Parte I: Construcción de la clave

1 Se lee el microdato Censo 2017 csv con la función import de la librería rio.

library("rio")
x <- import("Microdato_Censo2017-Personas.csv")

Hacemos un subset para trabajar mas rápido:

# x <- x[c(1:10000),]

El código se construye uniendo los siguientes elementos de la base de datos

COMUNA : Se mantiene igual. DC : Siempre debe tener dos digitos anteponiendo un cero si tiene uno. AREA : Se mantiene igual. ZC_LOC : Siempre debe tener tres digitos anteponiendo un cero si tiene dos y dos si tiene uno.

2 Analicemos la estructura del código de Comuna:

unique(x$COMUNA)

##   [1] 15202 15201 15102 15101 14204 14203 14202 14201 14108 14107 14106 14105
##  [13] 14104 14103 14102 14101 13605 13604 13603 13602 13601 13505 13504 13503
##  [25] 13502 13501 13404 13403 13402 13401 13303 13302 13301 13203 13202 13201
##  [37] 13132 13131 13130 13129 13128 13127 13126 13125 13124 13123 13122 13121
##  [49] 13120 13119 13118 13117 13116 13115 13114 13113 13112 13111 13110 13109
##  [61] 13108 13107 13106 13105 13104 13103 13102 13101 12402 12401 12303 12302
##  [73] 12301 12202 12201 12104 12103 12102 12101 11402 11401 11303 11302 11301
##  [85] 11203 11202 11201 11102 11101 10404 10403 10402 10401 10307 10306 10305
##  [97] 10304 10303 10302 10301 10210 10209 10208 10207 10206 10205 10204 10203
## [109] 10202 10201 10109 10108 10107 10106 10105 10104 10103 10102 10101  9211
## [121]  9210  9209  9208  9207  9206  9205  9204  9203  9202  9201  9121  9120
## [133]  9119  9118  9117  9116  9115  9114  9113  9112  9111  9110  9109  9108
## [145]  9107  9106  9105  9104  9103  9102  9101 16109 16207 16305 16108 16304
## [157] 16301 16206 16201 16107 16205 16106 16105 16303 16204 16104 16103 16302
## [169] 16203 16202 16102 16101  8314  8313  8312  8311  8310  8309  8308  8307
## [181]  8306  8305  8304  8303  8302  8301  8207  8206  8205  8204  8203  8202
## [193]  8201  8112  8111  8110  8109  8108  8107  8106  8105  8104  8103  8102
## [205]  8101  7408  7407  7406  7405  7404  7403  7402  7401  7309  7308  7307
## [217]  7306  7305  7304  7303  7302  7301  7203  7202  7201  7110  7109  7108
## [229]  7107  7106  7105  7104  7103  7102  7101  6310  6309  6308  6307  6306
## [241]  6305  6304  6303  6302  6301  6206  6205  6204  6203  6202  6201  6117
## [253]  6116  6115  6114  6113  6112  6111  6110  6109  6108  6107  6106  6105
## [265]  6104  6103  6102  6101  5804  5803  5802  5801  5706  5705  5704  5703
## [277]  5702  5701  5606  5605  5604  5603  5602  5601  5506  5504  5503  5502
## [289]  5501  5405  5404  5403  5402  5401  5304  5303  5302  5301  5201  5109
## [301]  5107  5105  5104  5103  5102  5101  4305  4304  4303  4302  4301  4204
## [313]  4203  4202  4201  4106  4105  4104  4103  4102  4101  3304  3303  3302
## [325]  3301  3202  3201  3103  3102  3101  2302  2301  2203  2202  2201  2104
## [337]  2103  2102  2101  1405  1404  1403  1402  1401  1107  1101

Vemos que algunos códigos tienen 5 digitos y otros 4. Vamos a dejar ésto inalterado . Sin embargo, añadimos un trozo de código si en el futuro se desea agregar un cero previo a las comunas de 4 dígitos para homologar.

# recogemos el campo Comuna:
codigos <- x$COMUNA
# construimos una secuencia llamada rango del 1 al total de filas del dataset:
rango <- seq(1:nrow(x))
# Creamos un string que agrega un cero a todos los registros:
cadena<- paste("0",codigos[rango], sep = "")

# El string cadena tiene o 5 o 6 digitos, los cuales siempre deben ser siempre 5 agregandole un cero al inicio de los que tienen 4.
# Para ello extraemos un substring de la cadena sobre todas las filas (rangos) comenzando desde el primero o el segundo y llegando siempre al 6.

cadena <- substr(cadena,(nchar(cadena)[rango])-(4),6)
codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
comuna_corr <- cbind(codigos,cadena)

Lo verificamos

head(unique(comuna_corr$cadena),50)

##  [1] "15202" "15201" "15102" "15101" "14204" "14203" "14202" "14201" "14108"
## [10] "14107" "14106" "14105" "14104" "14103" "14102" "14101" "13605" "13604"
## [19] "13603" "13602" "13601" "13505" "13504" "13503" "13502" "13501" "13404"
## [28] "13403" "13402" "13401" "13303" "13302" "13301" "13203" "13202" "13201"
## [37] "13132" "13131" "13130" "13129" "13128" "13127" "13126" "13125" "13124"
## [46] "13123" "13122" "13121" "13120" "13119"

3 Analicemos la estructura del código de DC:

head(unique(x$DC),50)

##  [1]  1  2  3  4 99  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
## [26] 25 26 27 28 29 30 31 32 33

Debemos agregar un cero a la izquierda a todos los códigos DC que contengan un dígito:

# Le asignamos a la variable codigos, la variable DC del dataframe x:
codigos <- x$DC

# Creamos una secuencia llamada rango con toda la cantidad de registros del dataframe:
rango <- seq(1:nrow(x))

# Creamos un string que añade un cero a todos los codigos quedando algunos con dos dígitos y otros con tres: 
cadena <- paste("0",codigos[rango], sep = "")

# Ésta es la línea más importante del código. 
# Si el string entrante contiene tres digitos, la función substr comenzaría desde la posición 2 a la 3, y si tiene 2, comenzaría desde la posición 1 a la 3, pero como no existe posición tres, llega a la 2.

cadena <- substr(cadena,(nchar(cadena)[rango])-(1),(nchar(cadena)[rango]))

codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
dc <- cbind(codigos,cadena)

Lo verificamos

head(unique(dc$cadena),50)

##  [1] "01" "02" "03" "04" "99" "05" "06" "07" "08" "09" "10" "11" "12" "13" "14"
## [16] "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29"
## [31] "30" "31" "32" "33"

4 Analicemos la estructura del código de zc_loc:

a002 <- head(unique(x$ZC_LOC),50)

kbl(a002) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "30%", height = "300px")

x
6
8
12
15
4
5
9
11
901
1
2
10
14
13
999
7
21
3
20
17
16
39
33
38
48
23
35
43
50
28
32
37
42
49
24
26
29
36
40
46
47
19
22
25
34
45
18
27
30
31

Deben todos los codigos poseer tres dígitos, agregándole un cero a los que tienen 2 y dos ceros a los que tienen uno.

codigos <- x$ZC_LOC
rango <- seq(1:nrow(x))
cadena<- paste("00",codigos[rango], sep = "")
cadena <- substr(cadena,(nchar(cadena)[rango])-(2),nchar(cadena)[rango])
codigos <- as.data.frame(codigos)
cadena <- as.data.frame(cadena)
cadena_c <- cbind(codigos,cadena)

6 lo verificamos

head(unique(cadena_c$cadena),50)

##  [1] "006" "008" "012" "015" "004" "005" "009" "011" "901" "001" "002" "010"
## [13] "014" "013" "999" "007" "021" "003" "020" "017" "016" "039" "033" "038"
## [25] "048" "023" "035" "043" "050" "028" "032" "037" "042" "049" "024" "026"
## [37] "029" "036" "040" "046" "047" "019" "022" "025" "034" "045" "018" "027"
## [49] "030" "031"

7 Unimos nuestra nueva clave a nuestro dataframe original con el nombre de campo clave:

x$clave <- paste(x$COMUNA, dc$cadena, x$AREA,  cadena_c$cadena, sep="")

Verificamos para los primeros 50 registros y vemos que la última columna contiene la clave.

Recordemos que:

COMUNA : Se mantiene igual.
DC : Siempre debe tener dos digitos anteponiendo un cero si tiene uno.
AREA : Se mantiene igual.
ZC_LOC : Siempre debe tener tres digitos anteponiendo un cero si tiene dos y dos si tiene uno.

tablamadre <- head(x,50)

kbl(tablamadre) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

REGION	PROVINCIA	COMUNA	DC	AREA	ZC_LOC	ID_ZONA_LOC	NVIV	NHOGAR	PERSONAN	P07	P08	P09	P10	P10COMUNA	P10PAIS	P11	P11COMUNA	P11PAIS	P12	P12COMUNA	P12PAIS	P12A_LLEGADA	P12A_TRAMO	P13	P14	P15	P15A	P16	P16A	P16A_OTRO	P17	P18	P19	P20	P21M	P21A	P10PAIS_GRUPO	P11PAIS_GRUPO	P12PAIS_GRUPO	ESCOLARIDAD	P16A_GRUPO	REGION_15R	PROVINCIA_15R	COMUNA_15R	P10COMUNA_15R	P11COMUNA_15R	P12COMUNA_15R	clave
15	152	15202	1	2	6	13225	1	1	1	1	1	73	1	98	998	3	15101	998	1	98	998	9998	98	2	4	6	2	1	2	98	7	98	98	98	98	9998	998	998	998	4	2	15	152	15202	98	15101	98	15202012006
15	152	15202	1	2	6	13225	3	1	1	1	1	78	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	3	1	2	2	2	78	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	1	1	3	1965	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	3	1	3	5	2	52	1	98	998	2	98	998	1	98	998	9998	98	1	2	5	2	1	2	98	7	98	2	1	4	1995	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	3	1	4	11	1	44	1	98	998	2	98	998	1	98	998	9998	98	1	3	5	2	1	2	98	1	Z	98	98	98	9998	998	998	998	3	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	9	1	1	1	1	39	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	8	98	98	98	98	9998	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	9	1	2	2	2	35	1	98	998	2	98	998	1	98	998	9998	98	2	6	5	2	1	2	98	1	Z	2	2	11	2004	998	998	998	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	9	1	3	5	1	13	1	98	998	2	98	998	1	98	998	9998	98	1	7	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	7	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	9	1	4	5	1	12	1	98	998	2	98	998	1	98	998	9998	98	1	6	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	10	1	1	1	2	65	1	98	998	2	98	998	1	98	998	9998	98	2	4	5	2	1	2	98	6	98	3	3	9	1992	998	998	998	4	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	13	1	1	1	1	50	1	98	998	2	98	998	1	98	998	9998	98	2	5	5	2	1	2	98	1	Z	98	98	98	9998	998	998	998	5	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	13	1	2	4	2	43	1	98	998	2	98	998	1	98	998	9998	98	2	6	5	2	1	2	98	6	98	2	2	3	2002	998	998	998	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	13	1	3	5	1	15	3	15201	998	2	98	998	1	98	998	9998	98	1	1	7	2	1	2	98	8	98	98	98	98	9998	998	998	998	9	2	15	152	15202	15201	98	98	15202012006
15	152	15202	1	2	6	13225	16	1	1	1	1	75	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	16	1	2	16	2	58	4	98	68	6	98	998	5	98	998	9999	1	3	98	98	98	1	2	98	7	98	4	4	99	9999	68	68	68	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	16	1	3	2	2	70	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	5	4	99	9999	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	1	1	2	43	2	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	I	3	3	9	2008	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	2	4	1	55	2	98	998	2	98	998	1	98	998	9998	98	2	6	5	2	1	2	98	6	98	98	98	98	9998	998	998	998	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	3	5	2	13	2	98	998	2	98	998	2	15101	998	9998	98	1	7	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	7	2	15	152	15202	98	98	15101	15202012006
15	152	15202	1	2	6	13225	17	1	4	5	1	8	2	98	998	2	98	998	2	15101	998	9998	98	1	2	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	2	2	15	152	15202	98	98	15101	15202012006
15	152	15202	1	2	6	13225	17	1	5	15	2	29	2	98	998	4	98	998	3	98	998	2015	1	2	6	5	2	1	2	98	6	98	5	5	11	2014	998	604	604	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	6	15	1	4	2	98	998	1	98	998	5	98	998	2015	1	1	0	1	2	1	2	98	98	98	98	98	98	9998	998	998	68	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	7	15	2	2	2	98	998	1	98	998	3	98	998	2015	1	1	0	1	2	1	2	98	98	98	98	98	98	9998	998	998	604	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	17	1	8	15	1	16	2	98	998	6	98	998	1	98	998	9998	98	2	4	5	2	1	2	98	6	98	98	98	98	9998	998	68	998	4	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	18	1	1	1	2	74	1	98	998	2	98	998	1	98	998	9998	98	2	2	5	2	1	2	98	6	98	2	2	12	1976	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	19	1	1	1	1	68	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	20	1	1	1	1	74	1	98	998	3	15101	998	1	98	998	9998	98	2	2	5	2	1	2	98	1	Z	98	98	98	9998	998	998	998	2	2	15	152	15202	98	15101	98	15202012006
15	152	15202	1	2	6	13225	20	1	2	2	2	65	1	98	998	3	997	998	3	98	998	9999	2	2	2	5	2	1	2	98	6	98	2	2	9	1982	998	998	604	2	2	15	152	15202	98	997	98	15202012006
15	152	15202	1	2	6	13225	25	1	1	1	2	76	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	6	98	8	6	3	1981	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	25	1	2	5	2	36	1	98	998	2	98	998	1	98	998	9998	98	2	4	8	1	1	2	98	1	A	0	98	98	9998	998	998	998	12	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	1	1	2	31	1	98	998	2	98	998	5	98	998	2007	2	2	5	5	2	1	2	98	1	A	2	2	4	2008	998	998	68	5	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	2	4	1	35	1	98	998	2	98	998	5	98	998	2007	2	2	6	5	2	1	2	98	1	F	98	98	98	9998	998	998	68	6	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	3	5	1	11	1	98	998	2	98	998	5	98	998	2007	2	1	5	5	2	1	2	98	98	98	98	98	98	9998	998	998	68	5	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	4	5	1	8	1	98	998	2	98	998	1	98	998	9998	98	1	2	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	28	1	5	15	2	74	1	98	998	2	98	998	1	98	998	9998	98	2	3	5	2	1	2	98	6	98	6	6	99	9999	998	998	998	3	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	33	1	1	1	1	41	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	Z	98	98	98	9998	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	33	1	2	2	2	47	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	1	A	2	1	4	1996	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	33	1	3	14	1	88	1	98	998	2	98	998	1	98	998	9998	98	3	98	98	98	1	2	98	7	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	33	1	4	14	1	65	1	98	998	2	98	998	1	98	998	9998	98	2	2	5	2	1	2	98	7	98	98	98	98	9998	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	1	1	2	59	1	98	998	2	98	998	1	98	998	9998	98	2	2	5	2	1	2	98	6	98	8	8	2	1998	998	998	998	2	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	2	2	1	56	1	98	998	99	99	999	1	98	998	9998	98	2	2	5	2	1	2	98	6	98	98	98	98	9998	998	999	998	2	2	15	152	15202	98	99	98	15202012006
15	152	15202	1	2	6	13225	36	1	3	5	2	36	1	98	998	2	98	998	1	98	998	9998	98	2	8	5	1	1	2	98	6	98	2	2	7	2010	998	998	998	8	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	4	12	2	13	1	98	998	2	98	998	1	98	998	9998	98	1	7	5	2	1	2	98	98	98	98	98	98	9998	998	998	998	7	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	5	12	2	6	1	98	998	2	98	998	1	98	998	9998	98	1	0	3	1	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	98	15202012006
15	152	15202	1	2	6	13225	36	1	6	5	1	24	1	98	998	3	15101	998	1	98	998	9998	98	2	4	7	1	1	2	98	1	Z	98	98	98	9998	998	998	998	12	2	15	152	15202	98	15101	98	15202012006
15	152	15202	1	2	6	13225	36	1	7	11	2	24	1	98	998	3	15101	998	1	98	998	9998	98	2	4	7	1	1	2	98	1	N	2	2	11	2015	998	998	998	12	2	15	152	15202	98	15101	98	15202012006
15	152	15202	1	2	6	13225	36	1	8	12	1	6	1	98	998	2	98	998	2	15101	998	9998	98	1	0	3	1	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	15101	15202012006
15	152	15202	1	2	6	13225	36	1	9	12	2	1	1	98	998	1	98	998	2	15101	998	9998	98	3	98	98	98	1	2	98	98	98	98	98	98	9998	998	998	998	0	2	15	152	15202	98	98	15101	15202012006
15	152	15202	1	2	6	13225	38	1	1	1	1	19	1	98	998	3	15101	998	2	15101	998	9998	98	1	1	8	2	1	2	98	1	A	98	98	98	9998	998	998	998	9	2	15	152	15202	98	15101	15101	15202012006
15	152	15202	1	2	6	13225	39	1	1	1	1	21	1	98	998	2	98	998	1	98	998	9998	98	2	1	7	2	1	2	98	1	F	98	98	98	9998	998	998	998	9	2	15	152	15202	98	98	98	15202012006

Observemos algunas claves:

unicas <- unique(x$clave)
codigos_unicos <- head(unicas,50)

kbl(codigos_unicos) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

x
15202012006
15202012008
15202012012
15202012015
15202022004
15202022005
15202022009
15202022011
15202022901
15202032001
15202032002
15202032010
15202032014
15202032901
15202042013
15202042901
15202992999
15201011001
15201012901
15201022002
15201032006
15201032007
15201032901
15201042009
15201042021
15201042901
15201052001
15201052003
15201052012
15201052013
15201052020
15201052901
15201062005
15201062010
15201062017
15201062901
15201072901
15201082004
15201991999
15102012002
15102012003
15102022007
15102032005
15102032008
15102032901
15102042001
15102052004
15102052006
15101011001
15101011002

Parte II: Generación de las tablas de contingencia:

El Censo 2017 contempla preguntas agrupadas por el prefijo P y un número. Comenzaremos con la P07:

P07 Relación de parentesco.

La categoria 19: “Persona en operativo calle” no figura en la base de datos.

tabla_P07 <- table(x$clave, x$P07, useNA = "no")

colnames(tabla_P07) <- c("Jefe/a de hogar","Esposo/a o cónyuge","Conviviente por unión civil","Conviviente de hecho o pareja","Hijo/a","Hijo/a del cónyuge, conviviente o pareja","Hermano/a","Padre/madre","Cuñado/a","Suegro/a","Yerno/nuera","Nieto/a","Abuelo/a","Otro pariente","No pariente","Servicio doméstico puertas adentro","Persona en vivienda colectiva","Persona en tránsito","Persona en operativo calle")

a001 <- head(tabla_P07,5)
kbl(a001) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Jefe/a de hogar	Esposo/a o cónyuge	Conviviente por unión civil	Conviviente de hecho o pareja	Hijo/a	Hijo/a del cónyuge, conviviente o pareja	Hermano/a	Padre/madre	Cuñado/a	Suegro/a	Yerno/nuera	Nieto/a	Abuelo/a	Otro pariente	No pariente	Servicio doméstico puertas adentro	Persona en vivienda colectiva
10101011001	186	39	0	27	46	6	8	6	1	1	3	12	1	12	29	3	204
10101011002	1067	336	16	107	739	18	60	37	14	10	37	171	1	129	109	2	88
10101021001	1341	453	15	183	1094	43	93	54	17	8	40	241	4	178	128	2	59
10101021002	343	130	0	17	189	3	23	16	5	7	5	37	0	53	39	12	228
10101021003	796	211	5	98	475	11	57	34	17	9	17	90	1	132	117	3	221

write.table(tabla_P07,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P07.xlsx")

P08 Sexo.

tabla_P08 <- table(x$clave, x$P08, useNA = "no")
colnames(tabla_P08) <- c("Hombre","Mujer")

#write_xlsx(tabla_P08, "tabla_P08.xlsx")

a_003 <- head(tabla_P08,50)
kbl(a_003) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Hombre	Mujer
10101011001	310	274
10101011002	1428	1513
10101021001	1962	1991
10101021002	547	560
10101021003	1174	1120
10101021004	1711	1680
10101021005	1252	1312
10101031001	2242	2288
10101031002	2390	2350
10101031003	2083	2024
10101031004	1426	1430
10101031005	2669	3021
10101031006	1242	1218
10101031007	1124	1168
10101031008	1714	1871
10101031009	2103	2333
10101031010	1709	1857
10101031011	1332	1425
10101031012	883	966
10101031013	1944	2001
10101031014	1081	1184
10101031015	916	1014
10101031016	1504	1567
10101031017	2371	1514
10101032002	63	66
10101032011	209	217
10101032019	399	430
10101041001	2090	2252
10101041002	1076	1093
10101041003	2556	2646
10101042010	4	2
10101051001	1182	1281
10101051002	963	950
10101051003	1590	1682
10101051004	1684	1949
10101061001	3231	3556
10101061002	1336	1393
10101061003	1763	1905
10101061004	1406	1589
10101061005	1250	1321
10101061006	1962	2168
10101061007	433	384
10101061008	1052	1057
10101061009	85	83
10101061010	768	775
10101062003	91	67
10101062008	280	301
10101062013	304	267
10101062029	23	24
10101062039	38	29

x_003 <- as.data.frame(a_003)
write_xlsx(x_003,"x_003.xlsx")

write.table(tabla_P08,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P08.xlsx")

P09 Edad.

tabla_P09 <- table(x$clave, x$P09, useNA = "no")
#write_xlsx(tabla_P09, "tabla_P09.xlsx")

a_004 <- head(tabla_P09,50)

kbl(a_004) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46	47	48	49	50	51	52	53	54	55	56	57	58	59	60	61	62	63	64	65	66	67	68	69	70	71	72	73	74	75	76	77	78	79	80	81	82	83	84	85	86	87	88	89	90	91	92	93	94	95	96	97	98	99	100
10101011001	3	2	2	3	6	2	0	1	1	1	0	2	3	1	2	6	5	9	3	8	11	7	8	8	13	12	24	10	16	11	6	12	12	10	13	12	6	9	7	4	3	13	7	10	8	1	5	8	8	8	8	6	8	8	15	7	9	11	9	15	3	12	9	6	10	7	5	3	3	5	9	6	4	8	6	6	5	2	2	4	0	2	4	5	5	2	3	2	2	2	0	0	1	0	0	1	0	0	0	1	1
10101011002	23	26	36	27	29	33	27	37	33	40	26	29	31	23	33	39	37	31	67	54	67	58	56	57	58	60	43	48	71	38	34	45	31	39	40	53	53	36	38	37	35	41	30	43	30	35	36	38	39	48	28	41	35	28	32	42	31	36	30	35	32	34	30	35	21	39	30	28	28	22	20	24	23	14	18	11	20	12	12	15	11	11	12	11	11	8	13	4	7	4	9	4	3	0	3	1	2	0	1	0	2
10101021001	34	41	38	43	42	39	45	43	40	50	49	41	39	42	47	46	60	48	56	60	70	83	61	71	95	77	83	69	75	64	60	58	61	50	46	46	32	43	41	50	47	37	53	62	50	54	50	40	54	46	67	52	64	57	52	58	59	56	53	52	49	39	55	40	31	25	37	32	31	34	31	28	22	24	18	30	21	27	22	25	15	18	16	9	9	8	8	8	8	6	4	6	5	4	2	0	1	1	1	0	2
10101021002	9	6	6	2	6	1	10	6	4	13	9	11	5	12	7	8	8	8	7	13	17	7	15	20	18	36	21	15	29	22	26	13	13	11	10	18	10	19	14	15	13	13	12	10	18	16	10	11	14	19	10	15	14	16	19	9	15	15	18	17	15	17	17	15	14	20	16	11	10	12	6	16	14	11	10	8	11	8	10	4	8	3	4	12	6	4	5	5	5	3	2	4	7	3	1	1	3	0	1	0	1
10101021003	28	18	20	15	10	21	11	17	17	12	14	14	20	18	18	23	24	30	33	48	52	47	46	61	53	48	44	50	50	26	36	36	38	32	30	28	38	22	23	25	22	17	24	31	32	22	40	28	30	30	37	24	41	31	31	28	32	28	30	29	25	32	22	21	20	26	24	18	24	19	18	21	14	13	23	15	14	16	12	12	13	13	7	15	13	7	15	11	7	6	5	1	3	3	2	0	0	0	0	0	1
10101021004	37	42	38	44	30	30	39	39	40	32	35	32	28	39	41	35	38	35	42	51	73	65	77	76	55	70	59	63	50	59	65	39	48	43	37	38	41	45	39	34	37	35	33	45	39	42	36	47	46	51	48	41	47	54	50	39	35	28	51	56	38	40	35	33	44	29	36	32	36	30	28	32	28	27	18	20	18	21	18	17	10	21	9	10	15	12	6	10	7	2	5	4	5	4	3	1	0	1	0	1	2
10101021005	31	32	26	29	34	30	42	27	29	47	38	38	27	26	30	30	29	37	37	43	36	50	48	46	34	48	44	46	48	45	54	37	30	30	31	30	33	41	37	40	42	38	29	36	38	37	32	29	40	36	49	54	45	34	39	22	38	28	33	31	24	22	23	16	27	23	17	14	13	16	12	8	14	4	15	5	12	11	8	10	6	11	9	6	2	3	6	5	3	6	1	2	3	2	2	0	1	1	0	0	1
10101031001	47	38	44	48	52	34	54	46	39	54	47	34	46	41	54	63	51	55	68	73	75	83	84	88	106	97	101	95	78	75	51	64	63	47	56	54	53	39	38	44	46	46	43	63	47	70	67	57	73	68	66	58	77	53	70	53	53	58	58	41	47	44	43	54	37	59	40	42	32	42	28	40	30	31	43	32	34	33	32	32	25	25	32	22	15	19	12	19	11	5	8	1	3	1	4	2	2	0	0	1	2
10101031002	63	63	54	77	61	48	65	78	59	69	49	60	57	57	76	57	79	75	72	84	74	74	109	93	84	113	86	105	99	74	67	57	50	86	66	72	70	74	66	62	60	68	60	64	64	69	58	68	66	82	69	72	88	64	59	43	50	61	60	52	46	33	34	44	35	26	27	33	28	40	22	20	18	24	15	13	24	14	12	14	5	9	4	5	4	5	4	4	4	3	2	2	2	2	0	1	0	1	0	0	0
10101031003	52	54	61	44	62	66	76	69	58	54	63	49	60	57	55	60	59	71	79	71	84	71	57	68	89	82	88	65	71	73	64	46	73	55	54	58	48	57	54	44	58	47	56	54	49	60	55	56	49	55	53	59	53	43	51	46	48	40	42	43	44	35	34	25	28	27	34	21	29	26	19	26	28	22	13	18	14	18	13	11	12	12	9	9	6	6	5	3	4	5	3	3	3	0	1	1	2	0	0	0	0
10101031004	38	32	27	40	31	32	40	30	29	32	22	35	29	34	41	29	41	47	41	37	54	61	49	51	54	58	49	59	38	34	50	31	40	33	39	33	24	30	27	24	29	28	25	42	39	41	33	24	39	36	36	33	37	43	39	40	41	35	42	19	33	34	34	23	31	34	20	28	30	26	25	31	19	23	23	18	23	27	8	17	11	16	7	23	9	12	12	4	6	7	4	3	2	1	0	2	1	1	1	0	1
10101031005	102	112	119	114	106	100	123	108	99	119	91	89	84	78	91	77	81	75	78	67	72	87	96	94	83	102	113	135	128	118	139	119	111	126	139	142	126	102	91	93	97	107	87	98	78	65	75	76	66	58	51	63	60	41	43	59	51	36	32	26	24	32	17	22	27	15	12	13	18	8	16	2	13	7	8	4	11	6	5	6	5	3	3	2	1	3	1	3	2	0	0	1	0	1	0	0	0	0	0	0	1
10101031006	47	56	42	36	30	49	30	38	29	30	34	28	29	25	28	26	19	28	31	39	25	48	50	49	61	57	65	78	74	75	64	48	69	51	49	49	35	44	33	28	30	36	24	25	21	19	32	30	25	31	29	27	30	34	24	30	19	11	20	25	23	11	14	15	10	13	13	11	4	5	11	7	7	8	10	4	4	6	6	4	4	2	8	0	2	1	2	0	2	1	0	0	0	2	0	0	0	0	0	0	2
10101031007	20	31	33	32	26	42	45	38	32	47	36	45	56	56	36	45	48	36	44	42	41	38	33	25	31	39	33	31	33	28	16	28	17	27	33	37	46	34	59	68	61	59	63	50	42	56	50	41	35	36	37	34	21	19	22	23	9	19	8	7	13	3	6	10	3	8	5	3	3	5	10	7	6	3	3	5	4	3	1	1	0	1	1	0	1	1	2	0	3	0	0	2	0	0	0	0	0	0	0	0	0
10101031008	43	54	37	47	42	52	45	54	63	75	90	64	77	67	72	80	67	76	56	60	79	65	59	63	49	52	53	49	42	38	42	36	34	47	48	40	48	67	41	60	65	81	77	89	87	86	83	73	60	64	50	65	47	51	31	26	22	26	30	20	27	16	10	13	18	19	11	9	14	5	8	6	6	5	7	5	3	3	5	7	2	4	4	5	0	2	1	1	0	0	1	0	1	1	0	0	0	0	0	0	0
10101031009	61	73	65	50	56	63	58	87	75	64	64	72	56	65	70	67	65	86	73	78	86	103	79	86	105	93	104	99	98	69	77	74	63	52	55	65	45	51	40	46	40	47	42	46	51	53	53	73	75	81	73	89	73	74	79	63	73	37	54	33	43	33	36	27	25	18	24	13	15	10	16	19	9	11	10	8	10	11	10	5	5	3	4	5	5	3	1	1	2	0	1	2	1	0	0	1	0	0	0	2	0
10101031010	57	47	63	53	44	50	59	48	55	49	66	47	54	58	60	64	51	54	53	51	64	57	69	68	89	87	83	74	78	62	56	44	47	51	32	50	26	29	36	27	28	27	28	34	41	28	42	39	60	54	64	66	80	65	49	63	63	46	52	39	46	32	31	31	29	28	14	13	10	21	12	10	9	12	10	15	7	7	9	3	3	2	7	1	5	2	6	1	0	3	2	0	2	1	0	1	0	0	0	1	0
10101031011	30	38	33	42	34	37	33	36	34	43	43	31	43	42	45	66	52	46	53	48	58	53	57	58	65	51	64	46	44	48	27	36	23	26	25	26	24	23	24	22	30	31	35	36	44	54	35	52	38	59	48	46	54	60	58	38	47	41	34	22	26	23	17	30	16	16	9	11	10	5	8	10	6	3	13	1	12	6	6	2	3	5	2	3	0	7	1	5	3	1	1	1	1	0	1	0	0	0	0	0	2
10101031012	19	25	18	25	18	19	30	20	23	35	32	38	38	46	29	37	34	33	43	25	32	20	37	30	30	29	29	31	21	17	18	21	20	21	22	20	14	23	13	28	36	28	32	41	41	35	49	44	37	32	32	37	36	19	30	26	21	19	18	16	9	11	14	7	7	8	12	8	10	9	3	6	6	7	5	4	5	3	3	2	3	4	1	1	3	0	3	1	0	0	0	1	0	0	0	0	0	0	0	0	1
10101031013	61	55	73	59	52	70	66	62	58	59	61	53	48	59	54	56	49	61	63	76	73	71	81	68	77	77	78	93	90	61	76	55	61	46	43	45	55	46	46	24	32	27	31	36	42	39	35	57	64	69	69	69	65	55	72	61	54	57	46	44	35	40	32	31	19	30	29	19	21	14	15	14	16	19	21	14	10	14	10	6	2	14	3	3	4	4	4	4	4	3	1	2	2	0	0	0	0	0	0	0	1
10101031014	23	30	25	35	26	19	29	29	33	28	31	25	22	26	20	31	36	34	36	38	42	49	32	53	54	37	46	47	42	27	36	34	29	23	23	24	31	34	27	16	19	23	18	24	17	22	22	30	29	40	43	60	43	36	50	41	48	32	37	34	28	28	28	27	27	20	13	15	15	8	14	6	16	7	5	8	5	6	5	5	4	6	3	1	3	3	2	0	2	2	0	2	0	0	0	0	0	1	0	0	0
10101031015	31	29	29	28	31	34	36	42	36	34	34	44	44	37	33	39	38	28	27	25	28	24	16	27	18	32	23	23	17	24	25	20	27	24	38	33	41	49	52	56	37	46	39	53	46	38	33	27	27	23	23	30	23	31	15	18	20	2	12	5	11	12	5	11	9	2	3	6	6	2	3	3	2	4	2	6	5	1	1	1	2	0	0	3	0	1	0	1	1	0	1	0	1	0	1	0	0	0	0	0	0
10101031016	58	43	44	45	46	49	55	65	64	48	41	57	71	46	53	44	50	61	56	45	44	40	51	52	46	49	53	55	50	57	48	42	43	46	47	41	50	41	30	36	41	46	37	34	43	57	45	56	49	35	52	45	52	41	40	29	36	46	36	25	23	25	10	10	12	12	12	15	14	8	10	11	8	9	11	12	9	8	5	7	3	6	2	2	5	0	2	1	1	6	2	1	1	1	0	0	0	0	0	0	0
10101031017	71	51	64	48	74	72	90	68	51	46	45	41	48	38	45	38	47	38	38	38	53	52	61	76	82	84	115	120	129	142	124	153	134	156	119	131	111	102	83	72	55	61	55	66	48	41	32	31	27	28	25	29	21	20	19	17	9	14	12	10	15	7	12	4	5	8	2	6	9	7	11	4	1	3	4	3	1	2	2	3	1	0	1	1	0	1	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0
10101032002	1	2	1	0	1	1	1	3	2	1	2	2	0	2	1	2	4	1	2	2	3	2	1	3	2	2	3	1	3	3	0	2	0	0	2	2	3	1	3	2	1	1	2	2	1	5	1	2	6	3	1	3	0	2	0	0	2	2	2	1	2	3	1	1	0	1	1	1	0	1	2	1	1	0	0	2	2	0	2	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0
10101032011	7	2	3	2	5	4	3	4	7	7	2	8	5	4	6	2	9	7	8	8	7	9	7	7	3	5	11	7	8	6	4	7	2	6	3	3	5	6	3	6	8	4	6	2	5	9	10	8	5	4	12	5	10	5	10	4	4	8	8	7	9	5	8	3	4	4	4	4	2	2	2	2	1	3	3	1	2	3	0	1	2	0	1	0	2	0	2	3	0	0	0	1	0	0	0	0	0	0	0	0	0
10101032019	15	8	12	10	13	11	9	15	10	6	11	14	12	8	11	12	16	17	13	13	12	13	15	14	14	10	23	8	13	10	14	15	9	14	9	10	7	6	10	7	13	9	13	12	18	9	15	17	15	10	19	10	18	11	12	17	7	10	3	13	5	8	13	5	4	4	8	8	4	6	2	6	4	3	4	5	3	2	0	0	0	0	3	0	1	0	6	1	2	1	1	0	0	0	0	0	0	0	0	0	0
10101041001	44	60	52	54	58	59	59	57	62	46	58	67	57	49	56	59	52	65	64	63	83	74	82	93	82	79	81	68	47	70	65	54	55	50	54	49	47	37	44	47	59	50	54	54	61	72	45	63	74	53	52	52	59	67	44	51	43	39	48	41	50	41	50	56	44	39	36	48	40	44	40	38	35	24	33	26	30	20	20	27	19	8	15	9	11	7	10	8	3	3	4	3	2	3	2	2	1	6	0	1	1
10101041002	34	19	26	23	23	23	36	34	22	29	33	33	32	22	33	26	29	27	27	21	41	33	50	36	47	49	38	44	39	36	29	27	28	31	22	24	19	23	21	22	15	27	20	31	26	22	36	28	37	26	37	28	36	29	35	34	29	30	24	25	25	14	17	19	25	8	22	7	9	15	16	10	8	11	13	18	12	11	16	12	6	14	14	8	7	8	6	4	4	4	4	4	3	4	2	1	0	0	1	0	1
10101041003	92	92	76	82	73	113	89	102	73	81	70	76	65	69	68	53	67	58	61	69	79	68	62	65	63	62	72	95	75	123	103	103	112	107	123	131	129	117	115	101	88	96	77	74	64	74	66	56	47	44	47	41	50	45	65	51	53	39	71	58	47	50	38	49	49	36	40	26	31	21	13	22	11	20	14	11	5	13	1	5	11	4	7	4	7	3	3	0	5	4	6	0	1	1	0	1	0	2	1	0	0
10101042010	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0
10101051001	22	22	19	20	19	14	23	23	22	27	22	28	27	24	30	27	22	25	23	18	30	26	38	28	31	42	53	45	27	40	28	14	34	33	28	32	28	31	30	31	29	27	30	34	38	37	34	38	26	47	33	35	51	41	42	40	45	44	23	42	31	37	37	37	23	19	20	21	15	24	20	22	14	15	19	20	21	21	17	21	15	16	23	15	15	15	13	13	8	11	8	3	1	3	2	1	1	0	1	1	2
10101051002	24	17	18	21	25	27	28	27	19	24	28	19	18	26	21	28	27	31	36	40	31	26	28	27	42	38	39	32	21	28	31	19	26	28	25	16	28	22	22	27	21	24	31	44	26	22	19	15	27	26	19	20	24	30	26	29	25	27	27	15	18	25	29	27	20	18	23	16	25	11	17	16	10	12	14	10	4	7	8	6	5	2	3	3	4	5	4	4	5	0	2	2	1	0	0	0	0	0	0	0	0
10101051003	35	43	43	29	37	33	47	37	33	34	46	37	46	31	56	36	60	48	63	55	54	52	64	41	64	57	49	51	48	43	49	43	45	38	43	39	33	36	37	31	37	52	38	44	45	47	40	46	43	53	43	41	35	43	36	31	28	32	35	32	46	35	34	35	35	36	35	41	37	32	32	24	34	24	30	21	20	26	13	12	15	9	16	8	8	6	9	4	5	4	4	4	3	2	2	2	1	0	0	0	1
10101051004	40	23	40	33	20	33	34	25	38	35	32	32	27	38	44	39	59	44	69	95	86	85	69	90	90	100	88	90	75	58	65	62	66	41	43	51	44	42	47	44	49	52	47	50	34	38	37	36	48	38	46	45	38	54	37	47	55	38	46	42	35	33	31	26	30	30	27	28	27	27	32	24	31	21	22	19	11	21	11	15	14	19	7	7	9	12	2	5	9	9	7	2	2	5	2	2	1	3	0	0	2
10101061001	115	114	142	114	134	117	134	136	123	106	79	108	106	95	84	74	99	100	64	69	83	87	84	71	101	82	128	113	116	115	124	160	134	138	177	172	178	194	164	156	170	155	145	148	134	114	77	90	65	72	62	61	60	66	53	52	46	42	35	44	35	24	26	27	22	23	23	21	23	20	13	11	12	11	9	17	15	9	9	6	11	4	3	3	6	1	2	4	0	3	2	4	0	1	1	0	0	0	0	0	5
10101061002	38	40	38	29	30	39	25	34	44	46	33	29	37	36	38	29	40	44	58	78	57	68	60	52	39	45	53	42	48	33	46	35	42	34	34	34	27	39	40	53	46	35	45	44	44	56	35	36	43	32	36	38	25	35	29	35	28	22	26	31	23	25	22	22	20	21	14	23	7	13	15	16	11	15	10	10	4	5	9	10	7	2	4	1	6	2	4	2	0	3	3	1	2	4	2	1	0	2	0	1	0
10101061003	56	37	40	37	34	37	35	39	48	44	32	42	32	40	38	56	44	41	73	65	79	86	82	59	75	77	82	72	54	59	49	53	32	39	34	43	41	33	28	44	55	33	43	44	45	40	53	37	45	56	57	42	50	49	58	46	43	31	35	49	49	42	34	41	45	41	34	55	44	49	28	28	36	31	23	27	20	21	9	19	10	9	7	11	5	7	9	5	6	6	3	3	0	4	2	1	0	0	0	0	2
10101061004	27	37	24	34	29	34	32	28	20	23	22	28	31	27	49	38	32	32	59	75	106	89	105	80	84	85	75	47	40	34	24	35	24	21	22	33	23	35	33	20	20	26	28	35	23	32	39	48	43	60	46	40	37	39	44	35	35	35	28	30	29	25	21	29	26	36	27	29	30	21	24	34	22	18	27	25	20	18	14	18	11	9	9	9	9	6	10	4	5	0	2	1	1	2	0	0	1	2	0	1	1
10101061005	30	26	29	37	34	44	35	39	35	40	32	52	38	37	46	46	44	55	33	48	47	35	39	44	39	41	31	28	42	25	28	28	25	32	32	28	36	34	38	44	41	39	38	59	49	42	46	55	47	57	44	50	42	36	36	30	34	22	32	19	23	21	27	26	19	8	11	13	10	11	10	8	9	8	6	10	7	6	4	4	3	4	6	3	2	3	4	1	2	1	2	2	0	1	1	0	1	0	0	0	0
10101061006	44	60	40	51	40	53	72	60	57	52	54	57	60	64	68	74	70	73	62	53	55	72	67	63	82	83	96	89	90	82	72	67	80	56	60	58	64	65	51	47	50	53	73	66	75	79	74	49	69	71	71	67	64	52	62	49	42	38	43	37	27	37	25	20	27	34	26	18	7	13	18	10	14	13	9	10	9	7	2	1	9	5	12	6	4	4	2	0	0	1	0	1	4	0	3	1	0	0	0	0	4
10101061007	13	18	12	19	7	14	12	17	10	11	10	17	11	13	9	12	21	3	11	13	11	10	17	12	10	18	16	14	16	21	16	4	5	10	11	13	7	19	9	8	15	10	6	6	10	14	13	13	16	15	12	15	19	13	9	9	12	10	12	4	3	7	5	7	3	2	7	3	4	1	2	3	1	4	1	6	5	4	3	4	1	1	2	1	1	2	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0
10101061008	46	49	57	40	48	47	30	50	44	32	41	29	36	25	26	31	25	31	29	23	20	28	18	23	13	30	32	33	41	43	49	62	46	53	62	58	58	50	43	43	46	39	33	38	35	25	33	20	17	23	27	23	17	21	17	11	17	15	6	5	6	13	11	4	8	2	2	7	3	3	5	2	4	4	2	5	2	1	3	1	2	0	0	0	0	3	2	0	0	0	1	0	0	0	0	0	0	1	0	0	0
10101061009	3	2	5	4	2	4	1	6	1	2	5	2	2	2	3	4	4	2	3	3	2	4	8	3	2	6	2	2	1	1	0	3	2	1	0	2	6	2	1	2	3	1	3	3	2	1	4	1	3	3	5	0	1	4	2	2	0	2	3	1	3	2	2	0	0	0	0	1	1	1	1	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101061010	19	23	18	27	24	25	30	33	31	31	17	25	21	19	27	29	30	28	26	29	27	27	24	23	22	35	29	18	22	17	21	20	11	22	22	17	22	24	24	22	18	24	21	20	32	24	24	21	25	28	19	22	18	21	22	17	19	11	8	19	17	16	10	7	7	10	11	7	5	10	7	5	4	8	6	9	2	4	6	6	4	1	5	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0
10101062003	3	2	3	2	5	1	1	1	4	1	0	1	1	2	1	1	4	4	0	2	0	0	4	4	1	0	2	0	1	1	1	2	3	3	3	3	5	1	1	2	1	3	3	2	3	1	2	2	5	0	1	5	0	5	4	4	3	3	2	2	3	2	3	2	1	3	1	0	1	2	1	0	1	0	1	1	2	2	0	0	0	0	0	1	1	0	0	2	0	0	0	1	0	0	0	0	0	0	0	0	0
10101062008	4	11	6	11	6	9	14	6	10	9	12	10	10	7	6	9	6	6	9	4	5	9	4	7	6	7	3	8	4	3	6	12	7	3	7	12	12	10	9	13	8	5	9	8	14	11	14	11	10	12	7	15	6	11	8	4	8	9	8	7	9	3	3	5	2	4	5	5	3	5	4	3	5	4	4	2	1	1	0	1	2	4	0	1	1	2	1	2	0	0	0	0	1	1	0	0	0	0	0	0	0
10101062013	3	10	8	4	12	7	6	6	5	10	13	10	6	15	12	9	13	10	9	4	7	11	5	4	9	10	6	14	7	5	6	3	5	9	9	6	3	6	15	3	8	5	10	3	12	7	11	15	14	10	7	11	12	12	8	7	10	6	4	6	5	5	9	4	6	8	6	4	1	3	4	0	2	1	3	2	0	1	2	1	2	0	1	0	1	1	1	2	1	0	0	0	1	1	0	0	0	0	0	0	0
10101062029	0	0	1	0	0	0	1	1	0	0	0	0	0	1	1	0	0	1	1	0	0	1	0	1	0	0	4	2	2	0	0	1	1	0	0	0	1	0	0	0	1	0	0	0	1	1	1	2	2	1	1	1	1	3	0	0	0	0	2	0	1	1	2	0	0	1	0	1	0	1	0	1	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062039	2	0	2	0	0	2	0	0	1	0	0	0	0	0	2	0	1	1	0	3	2	3	1	2	2	1	1	3	1	0	0	0	0	2	0	0	0	1	0	0	0	0	2	2	0	1	0	1	0	0	2	2	1	2	3	0	0	1	2	3	1	2	1	1	0	0	1	2	0	1	0	0	0	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

write.table(tabla_P09,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P09.xlsx")

P10 Residencia habitual.

tabla_P10 <- table(x$clave, x$P10, useNA = "no")
colnames(tabla_P10) <- c("En esta vivienda","En otra vivienda","En otra comuna","En otro país","Missing")
#write_xlsx(tabla_P10, "tabla_P10.xlsx")

a_005 <- head(tabla_P10,50)

kbl(a_005) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	En esta vivienda	En otra vivienda	En otra comuna	En otro país	Missing
10101011001	351	58	89	80	6
10101011002	2734	96	64	24	23
10101021001	3702	114	95	7	35
10101021002	844	81	155	22	5
10101021003	1934	180	150	8	22
10101021004	3149	103	79	26	34
10101021005	2329	112	90	1	32
10101031001	4218	111	126	3	72
10101031002	4465	158	88	3	26
10101031003	3942	86	43	3	33
10101031004	2688	96	51	2	19
10101031005	5452	77	95	10	56
10101031006	2193	89	133	0	45
10101031007	2200	35	29	1	27
10101031008	3452	54	54	3	22
10101031009	4230	95	75	1	35
10101031010	3394	86	51	5	30
10101031011	2633	31	33	3	57
10101031012	1755	29	34	1	30
10101031013	3759	51	45	2	88
10101031014	2148	51	45	4	17
10101031015	1850	29	40	0	11
10101031016	2938	42	69	0	22
10101031017	2710	850	288	1	36
10101032002	125	1	1	0	2
10101032011	410	7	2	0	7
10101032019	804	11	9	0	5
10101041001	4138	92	62	4	46
10101041002	2039	62	39	3	26
10101041003	4815	207	109	6	65
10101042010	4	0	0	0	2
10101051001	2165	156	92	9	41
10101051002	1799	44	50	6	14
10101051003	3111	61	40	0	60
10101051004	3347	94	103	2	87
10101061001	6394	114	216	16	47
10101061002	2528	58	116	2	25
10101061003	3382	137	100	3	46
10101061004	2819	67	62	4	43
10101061005	2460	46	53	0	12
10101061006	3877	62	138	16	37
10101061007	789	4	17	0	7
10101061008	2009	36	50	1	13
10101061009	155	12	1	0	0
10101061010	1476	27	19	0	21
10101062003	150	2	3	0	3
10101062008	555	6	17	2	1
10101062013	519	30	12	1	9
10101062029	45	1	0	0	1
10101062039	65	1	1	0	0

write.table(tabla_P10,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P10.xlsx")

Demografía geográfica.

P10COMUNA Comuna de residencia habitual.

98: No aplica 99: Missing

tabla_P10COMUNA <- table(x$clave, x$P10COMUNA)

#write_xlsx(tabla_P10COMUNA, "tabla_P10COMUNA.xlsx")

a_006 <- head(tabla_P10COMUNA,50)

kbl(a_006) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	98	99	997	1101	1401	2101	2102	2201	2203	3101	3102	3202	3304	4101	4102	4106	4201	4203	4204	4301	5000	5101	5103	5105	5107	5109	5201	5301	5303	5401	5501	5502	5504	5506	5601	5602	5603	5605	5701	5704	5801	5802	5803	5804	6101	6103	6108	6113	6115	6116	6117	6301	6302	6303	6307	6310	7000	7101	7105	7109	7201	7202	7301	7302	7304	7308	7401	7402	7403	7404	7406	7408	8000	8101	8102	8103	8104	8106	8107	8108	8110	8111	8112	8201	8202	8206	8207	8301	8303	8304	8305	8306	8311	8313	9000	9101	9103	9104	9105	9107	9108	9109	9111	9112	9113	9114	9115	9116	9118	9119	9120	9201	9202	9203	9205	9209	9210	9211	10000	10102	10103	10104	10105	10106	10107	10108	10109	10201	10202	10203	10205	10206	10207	10208	10209	10210	10301	10302	10303	10304	10305	10306	10307	10401	10402	10403	10404	11000	11101	11201	11202	11203	11302	11401	11402	12000	12101	12301	12401	12402	13000	13101	13102	13103	13104	13105	13106	13107	13108	13109	13110	13111	13112	13113	13114	13115	13116	13117	13118	13119	13120	13121	13122	13123	13124	13125	13126	13127	13128	13129	13130	13132	13201	13203	13301	13302	13401	13402	13404	13501	13503	13601	13602	13603	13604	13605	14101	14102	14103	14104	14105	14106	14107	14108	14201	14202	14203	14204	15101	16101	16102	16103	16104	16106	16107	16109	16203	16301	16303
10101011001	489	6	0	3	0	3	0	0	0	0	0	0	0	3	0	0	1	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	1	0	0	0	0	2	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	2	0	0	0	0	0	3	0	1	0	1	0	0	2	0	1	4	0	1	3	0	1	0	1	0	1	3	0	0	0	0	12	0	0	0	0	0	0	0	0	2	0	0	0	3	0	0	0	1	0	1	0	1	5	2	1	0	0	1	0	1	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101011002	2854	23	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	1	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	3	5	1	0	0	0	0	2	2	1	2	0	0	0	0	1	0	0	1	1	0	0	3	0	1	0	0	0	0	2	3	0	0	0	0	2	0	0	0	0	0	0	0	0	2	0	0	0	3	0	0	0	1	3	1	0	0	2	2	0	0	0	0	0	0	1	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0
10101021001	3823	35	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	2	0	0	0	4	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	9	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	4	0	0	1	1	0	2	4	1	3	0	0	0	0	2	0	0	5	0	0	0	0	0	0	1	2	5	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	10	0	0	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	4	0	0	0	0	0	0	6	0	0	0	0	0	0	4	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101021002	947	5	3	1	0	4	0	0	0	0	0	0	0	3	0	0	0	0	1	0	0	2	0	0	0	5	0	2	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	2	1	0	0	4	1	0	0	0	0	0	4	0	1	0	0	0	0	1	0	0	0	0	0	0	1	6	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	7	1	0	2	2	1	1	1	7	1	1	0	2	2	1	0	0	2	0	1	0	0	0	0	1	0	3	0	0	0	1	1	0	0	0	0	0	13	0	0	0	0	20	0	1	0	0	1	0	0	1	4	0	0	0	1	0	1	0	1	3	0	0	2	2	1	2	0	0	0	0	1	0	3	0	0	0	0	0	0	0	0	2	0	0	1	1	4	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0
10101021003	2122	22	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	1	0	0	0	0	0	0	0	0	3	0	0	0	0	0	3	0	1	0	0	0	0	0	0	0	1	0	0	0	0	1	0	1	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	3	3	0	0	0	0	0	3	0	0	0	0	0	0	4	2	0	0	2	0	0	0	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	3	6	2	11	0	5	2	1	2	2	0	3	0	0	1	1	0	0	3	0	2	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	13	1	1	2	2	2	2	0	0	3	0	0	1	0	0	0	0	1	6	1	0	1	2	0	1	0	0	0	0	3	1	2	0	1	0	0	0	0	0	0	0	0	0	0	0	8	0	0	0	0	0	1	0	2	0	0	1	1	1	0	0	0	0	0	0	0	0	0
10101021004	3278	34	1	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	0	5	2	0	0	1	0	2	5	5	1	1	0	0	0	1	0	0	2	5	1	1	0	0	1	2	0	3	0	0	3	0	0	1	1	0	0	0	0	0	1	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	3	0	1	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	1	0	1	0	0	0	1	1	0	0	0	0	0	0	0	0	0
10101021005	2442	32	0	0	0	1	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	3	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	4	0	0	0	0	0	0	2	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	4	1	1	3	2	3	5	2	0	0	1	0	0	2	0	0	1	0	3	0	1	0	0	1	0	3	0	0	0	1	0	0	0	0	0	0	0	0	2	1	0	6	0	0	1	2	0	0	0	0	0	0	0	4	4	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	2	0	0	0	2	0	0	0	0	0	0	0	1	0	0	0	1	1	0	0	0	0	0	0	0	0	0
10101031001	4332	72	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	8	1	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	1	0	0	2	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	7	3	2	1	6	0	9	3	3	2	0	0	0	0	9	0	0	6	1	4	0	0	0	0	1	0	4	1	0	5	0	0	0	0	0	0	0	2	0	0	0	0	9	0	0	0	1	1	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	6	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101031002	4626	26	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	3	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	6	3	1	1	1	1	3	1	2	3	0	1	0	0	1	0	0	4	0	0	0	1	0	0	1	0	4	0	0	1	3	0	4	0	0	0	0	3	0	3	0	1	3	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	1	2	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1	0	0	0	0	0	0	4	0	0	0	0	0	2	0	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0
10101031003	4031	33	0	0	0	2	0	0	0	0	0	0	0	0	1	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	1	0	0	0	1	2	0	0	0	2	0	0	1	1	1	4	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	3	0	1	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0
10101031004	2786	19	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	3	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	0	1	1	3	1	1	0	0	1	0	0	4	1	0	4	0	1	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	4	0	0	0	0	8	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0
10101031005	5539	56	6	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	1	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	1	0	0	10	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	4	0	2	0	2	4	6	3	1	0	2	0	0	3	0	1	3	0	4	0	0	0	0	2	1	4	0	0	0	0	0	5	0	1	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	2	1	0	0	0	0	1	0	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0
10101031006	2282	45	1	1	0	6	0	2	0	3	1	0	1	0	4	0	0	0	0	0	0	5	0	0	0	2	0	1	0	0	0	0	0	0	5	0	0	0	0	0	6	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	1	1	0	0	0	0	3	3	1	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	2	0	3	1	0	0	4	4	6	4	2	0	1	1	1	3	3	2	0	0	1	0	1	0	1	0	3	0	0	0	5	0	0	0	0	0	0	3	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	1	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	8	0	0	0	0	1	1	0	1	0	0	1	0	1	1	0	0	0	0	0	1	0	0
10101031007	2236	27	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	0	0	0	3	2	0	1	0	0	0	0	0	2	0	4	0	0	0	1	0	0	0	0	3	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0
10101031008	3509	22	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	4	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	1	1	3	0	5	1	0	2	0	0	0	0	0	0	0	3	0	0	0	0	0	1	0	0	2	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	7	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	1	0	1	0	1	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0
10101031009	4326	35	4	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	5	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	1	1	0	3	2	3	0	1	1	0	0	0	0	3	1	0	5	1	2	0	0	0	0	2	0	4	0	0	1	0	0	2	0	1	0	0	4	0	2	0	0	2	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	1
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10101051002	1849	14	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	4	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	0	1	2	4	1	1	0	2	0	0	4	0	0	0	1	0	0	1	0	0	0	1	0	2	0	0	1	0	0	0	0	0	0	0	2	0	0	0	0	5	0	0	0	0	0	0	0	0	1	3	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101051003	3172	60	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	0	1	0	3	0	0	1	2	1	0	0	0	0	2	0	0	1	0	0	0	1	0	0	1	1	1	0	0	0	0	0	0	0	0	0	0	3	0	0	0	1	1	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	0
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10101061002	2588	25	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	3	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	4	6	1	1	0	2	1	0	2	9	8	1	3	0	1	2	2	1	11	3	1	4	0	0	0	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	1	4	0	0	0	0	1	0	0	0	4	0	0	1	2	2	0	0	0	0	0	0	2	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	0	1	0	2	1	0	1	0	0	1	0	1	0	0	0	0	0	0
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10101061004	2890	43	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	3	0	0	1	4	1	2	2	6	3	1	0	0	0	0	0	0	7	0	0	0	0	0	0	0	0	0	1	0	3	1	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0
10101061005	2506	12	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	2	0	2	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	0	1	1	4	1	0	0	0	0	0	0	0	1	0	0	1	1	1	0	0	0	0	0	0	1	0	0	2	0	1	0	0	0	0	0	1	0	0	0	0	8	0	0	0	0	0	2	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	2	1	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101061006	3955	37	2	1	0	0	0	0	0	0	0	0	0	2	1	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	3	0	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8	0	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	3	1	0	0	2	2	0	4	4	3	1	0	0	0	2	5	0	4	0	0	0	0	0	0	0	3	2	0	0	4	3	0	6	0	0	0	0	5	0	0	0	0	16	0	0	0	0	0	2	0	1	0	0	0	3	2	0	2	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	1	2	0	0	0	0	0	0	0	0	1	7	0	0	1	0	0	0	0	5	0	3	1	0	1	0	0	0	0	0	0	0	1	0
10101061007	793	7	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	0	0	1	0	2	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	0	0	2	1	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101061008	2046	13	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	3	3	0	0	1	0	0	6	1	3	0	0	0	0	0	0	0	4	0	1	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	2	1	1	0	0	0	0	2	0	2	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0
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10101061010	1503	21	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062003	152	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062008	563	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	2	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062013	550	9	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0
10101062029	46	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062039	66	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

write.table(tabla_P10COMUNA,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P10COMUNA.xlsx")

P11COMUNA Comuna de residencia de hace 5 años.

tabla_P11COMUNA <- table(x$clave, x$P11COMUNA, useNA = "no")
#write_xlsx(tabla_P11COMUNA, "tabla_P11COMUNA.xlsx")


a_007 <- head(tabla_P11COMUNA,50)

kbl(a_007) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	98	99	997	1000	1101	1107	1401	1404	2101	2102	2104	2201	2301	2302	3000	3101	3102	3201	3202	3301	3303	4101	4102	4105	4106	4201	4202	4203	4301	4303	4304	4305	5000	5101	5102	5103	5105	5107	5109	5201	5301	5303	5304	5401	5403	5404	5501	5502	5504	5506	5601	5602	5603	5604	5605	5701	5702	5703	5704	5705	5706	5801	5802	5803	5804	6101	6102	6103	6104	6107	6108	6110	6112	6113	6115	6116	6117	6201	6202	6203	6204	6205	6301	6302	6303	6305	6308	6309	6310	7000	7101	7102	7103	7105	7109	7201	7202	7203	7301	7304	7306	7307	7308	7401	7402	7403	7404	7405	7406	7408	8000	8101	8102	8103	8104	8105	8106	8107	8108	8109	8110	8111	8112	8201	8202	8203	8204	8205	8206	8207	8301	8302	8303	8304	8305	8306	8307	8308	8309	8311	8312	8313	9000	9101	9102	9103	9104	9105	9106	9107	9108	9109	9110	9111	9112	9113	9114	9115	9116	9117	9118	9119	9120	9121	9201	9202	9203	9205	9206	9207	9208	9209	9210	9211	10000	10102	10103	10104	10105	10106	10107	10108	10109	10201	10202	10203	10204	10205	10206	10207	10208	10209	10210	10301	10302	10303	10304	10305	10306	10307	10401	10402	10403	10404	11101	11102	11201	11202	11203	11301	11302	11401	11402	12000	12101	12104	12201	12202	12301	12302	12401	13000	13101	13102	13103	13104	13105	13106	13107	13108	13109	13110	13111	13112	13113	13114	13115	13116	13117	13118	13119	13120	13121	13122	13123	13124	13125	13126	13127	13128	13129	13130	13131	13132	13201	13202	13203	13301	13302	13303	13401	13402	13403	13404	13501	13502	13503	13504	13505	13601	13602	13603	13604	13605	14000	14101	14102	14103	14104	14105	14106	14107	14108	14201	14202	14203	14204	15101	16101	16102	16103	16104	16106	16107	16108	16109	16201	16202	16203	16204	16205	16206	16301	16302	16303	16305
10101011001	397	9	1	0	1	0	0	0	2	1	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	13	1	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	10	0	0	0	0	0	1	1	1	0	0	0	0	0	1	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	1	3	1	0	0	2	1	3	4	11	3	1	0	2	0	0	1	0	0	12	0	3	0	1	0	0	1	2	0	2	2	0	2	0	0	0	0	1	0	0	3	0	0	0	0	0	1	1	16	0	0	1	1	1	0	0	0	2	0	0	0	2	0	0	1	0	0	0	0	2	6	3	1	0	0	1	0	2	0	2	2	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	9	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0
10101011002	2290	59	10	0	5	0	0	0	8	1	0	0	0	0	0	3	1	0	0	0	0	3	0	0	0	0	0	1	2	0	0	0	0	8	0	2	0	1	24	0	1	0	0	3	0	0	1	3	0	0	1	0	0	0	0	0	0	1	0	0	0	5	0	0	1	4	0	0	2	0	0	0	0	0	0	0	1	0	0	0	0	0	3	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	4	1	0	0	0	0	0	0	11	4	2	0	0	0	1	0	0	15	3	1	0	1	0	0	0	1	1	4	0	1	0	0	0	0	0	0	0	0	0	0	15	0	1	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	0	3	0	0	0	0	0	0	0	1	0	18	6	7	8	6	12	6	8	18	30	32	7	2	8	4	2	8	8	11	26	2	0	0	1	0	0	3	2	14	1	5	0	3	1	1	0	0	0	0	2	42	0	0	1	5	0	5	0	42	1	0	1	2	0	1	1	3	2	0	0	0	4	0	0	0	1	7	1	0	0	0	1	1	0	0	0	0	0	0	2	1	0	0	0	5	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	9	0	0	0	0	0	0	0	4	2	0	2	2	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0
10101021001	3376	71	8	0	1	0	0	0	1	0	0	8	0	0	0	0	0	0	0	0	0	3	1	0	0	0	0	0	0	0	0	0	0	12	0	0	0	4	8	0	0	0	0	0	0	0	2	1	0	0	5	0	0	0	0	0	0	0	0	0	1	2	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	5	0	0	0	0	0	0	3	0	1	4	0	0	0	0	0	1	3	0	3	0	0	0	0	0	0	0	0	0	0	0	1	23	0	1	0	0	0	0	0	0	0	1	0	0	0	1	2	1	0	0	1	0	0	0	0	0	0	0	0	0	0	1	6	28	7	9	10	10	2	13	14	18	24	6	0	5	1	1	8	2	0	23	3	10	1	4	3	2	2	2	15	0	3	0	8	1	1	0	0	0	1	0	8	0	0	0	2	0	0	0	47	0	0	0	1	0	0	0	2	5	0	0	0	1	1	0	0	3	5	0	0	1	1	6	0	0	3	0	1	0	0	0	9	0	0	1	0	0	2	0	0	0	6	0	0	0	0	0	0	0	0	6	0	21	0	0	0	0	0	1	1	2	1	5	5	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101021002	813	8	6	0	2	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	7	0	0	0	0	9	0	2	0	0	0	0	0	0	0	0	0	1	0	2	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	3	0	1	0	0	0	0	0	2	1	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	0	0	1	0	0	2	0	1	0	0	9	0	0	0	0	0	0	0	0	6	0	1	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	1	0	0	1	12	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	1	0	2	0	1	0	0	0	0	0	0	0	2	0	2	7	4	0	3	3	1	4	3	8	5	2	0	2	2	2	7	0	0	6	0	1	0	0	0	0	1	0	5	0	1	0	1	1	0	0	0	0	0	0	10	0	0	0	0	0	0	0	49	0	2	0	2	0	0	3	1	1	2	0	0	7	0	1	0	0	3	2	0	3	6	0	1	0	0	0	0	3	0	0	3	0	0	1	1	0	3	0	1	1	1	0	0	0	0	2	1	0	2	0	0	6	0	0	0	0	0	0	0	4	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101021003	1747	52	14	0	9	2	0	0	2	0	0	3	0	0	0	1	0	0	0	0	0	2	0	1	0	0	0	0	1	0	0	0	0	5	0	0	0	0	6	0	1	1	0	0	0	0	0	0	0	0	3	0	0	0	0	1	0	0	0	0	3	4	0	1	1	2	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0	5	0	0	0	0	0	0	1	1	0	0	1	0	1	0	0	0	0	0	0	0	11	3	2	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	1	7	0	1	0	0	2	0	0	0	0	0	0	0	13	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	1	5	7	1	6	2	4	2	15	16	15	28	5	4	8	2	7	13	9	4	37	1	1	0	2	0	0	3	0	5	1	0	0	8	3	1	0	0	0	0	0	10	0	0	0	0	0	0	0	40	0	1	5	4	2	2	0	1	8	1	2	2	3	0	0	0	2	8	4	0	5	3	4	2	1	0	0	0	0	1	0	3	0	0	1	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	12	0	0	0	0	0	3	2	5	2	1	1	2	5	1	0	1	0	0	0	1	2	0	0	0	0	0	0	0	0	0
10101021004	2856	83	10	0	8	1	0	0	2	0	0	1	0	0	0	0	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	8	0	0	0	1	5	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	1	7	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	2	1	0	0	0	0	0	0	4	1	0	0	1	4	0	0	1	0	1	0	0	5	2	0	2	0	0	1	1	0	8	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	6	0	0	2	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	3	1	0	2	0	0	0	0	0	0	0	0	2	17	5	2	3	7	5	11	18	26	16	2	0	3	0	2	12	1	4	31	5	9	0	1	2	1	2	0	18	2	11	0	5	0	4	0	0	0	0	0	11	2	0	0	0	0	4	0	47	0	1	0	0	0	0	3	0	1	3	2	1	1	0	0	0	0	2	1	0	1	0	0	0	0	0	2	0	0	1	0	3	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	10	0	1	0	0	2	1	2	2	0	2	2	1	3	0	0	0	0	0	0	0	0	0	1	0	0	0	4	0	0	0
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10101031001	3794	127	27	0	0	0	0	0	8	0	0	4	0	0	0	2	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	9	1	0	2	0	0	1	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	2	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	1	0	0	0	0	0	6	0	0	0	0	0	0	0	2	0	0	0	0	2	0	0	0	0	0	0	0	27	1	1	0	1	0	0	0	1	2	0	0	1	0	0	0	1	2	0	1	0	0	0	0	0	0	0	0	1	0	1	0	17	0	2	1	0	0	0	1	1	0	0	0	0	3	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	6	26	8	12	3	36	14	32	23	15	22	2	0	8	0	0	20	2	3	29	1	5	1	1	0	2	3	1	13	1	4	0	6	1	1	0	0	0	0	0	9	0	0	0	4	0	0	0	51	0	0	0	1	2	0	1	3	1	0	0	0	7	0	0	0	0	1	3	0	0	0	0	0	0	1	1	4	2	1	0	4	0	0	0	0	0	1	0	0	1	1	0	0	0	0	0	0	0	0	0	0	21	0	2	4	0	1	3	1	6	1	2	9	3	6	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0
10101031002	4014	98	16	0	5	1	1	0	5	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	10	0	0	0	1	2	2	1	0	0	0	0	0	0	1	0	0	1	1	0	0	0	1	0	0	0	0	0	4	0	0	3	3	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0	0	0	1	7	0	0	0	0	0	0	0	17	0	1	0	0	0	1	0	0	3	3	0	0	1	0	0	0	1	0	7	0	0	0	0	0	0	0	0	0	0	0	3	21	1	0	1	0	0	1	0	1	0	3	1	0	0	0	0	3	0	1	6	0	0	0	0	0	0	0	0	0	2	0	4	22	5	17	8	25	7	20	33	18	23	0	2	3	0	0	9	7	3	24	4	9	1	3	1	0	2	1	12	3	10	0	12	0	7	0	0	0	0	0	17	0	0	0	0	0	0	0	54	2	0	2	4	4	1	0	0	4	0	0	0	0	0	0	1	0	7	4	2	1	0	0	3	4	0	0	1	0	1	0	2	0	0	0	0	1	4	0	0	0	0	0	1	0	0	0	0	0	0	0	0	18	0	0	4	0	0	1	4	6	4	3	12	3	2	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0
10101031003	3627	144	14	0	4	1	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	2	7	0	2	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	3	1	0	0	0	0	0	0	0	0	1	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	6	1	1	0	0	0	0	0	0	3	0	1	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	1	1	0	1	0	0	0	1	0	1	2	0	0	2	0	3	0	0	0	0	0	0	0	0	0	0	0	2	18	2	6	7	18	2	9	10	3	12	1	0	2	0	0	8	1	1	29	5	3	3	3	1	0	0	0	9	0	1	0	3	3	0	0	0	0	0	0	9	0	0	0	0	0	2	0	25	0	0	2	0	0	0	0	0	2	1	2	0	0	0	0	0	0	7	3	0	1	0	0	2	1	0	0	0	1	2	0	2	0	0	0	1	0	2	0	0	1	0	0	0	0	0	0	0	0	0	0	1	6	0	0	2	0	0	0	2	10	1	1	1	1	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0
10101031004	2406	132	13	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	8	0	0	0	0	5	0	0	0	0	0	0	0	1	2	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	1	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	7	0	0	0	1	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	11	5	4	6	12	1	13	6	10	7	3	0	6	0	1	7	2	1	18	0	3	0	4	1	0	0	0	19	0	4	0	8	1	0	1	0	0	0	3	16	0	0	0	0	0	0	0	33	0	0	4	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	3	0	0	0	0	0	0	0	3	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	14	3	0	0	0	0	0	0	1	1	3	6	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101031005	4828	100	17	0	9	0	1	0	18	0	0	3	0	0	0	0	0	0	0	0	0	10	0	0	0	0	0	0	0	0	0	0	0	13	0	0	0	0	25	0	0	0	0	2	0	0	0	0	0	0	11	0	1	0	0	0	0	0	0	0	0	3	1	0	1	9	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	14	4	0	5	2	1	0	0	0	8	2	4	5	2	1	0	0	1	0	1	0	0	0	1	0	0	0	0	0	0	0	0	35	0	2	0	0	0	0	0	2	0	0	2	0	1	0	0	0	2	0	5	0	0	0	0	0	0	0	0	0	0	3	6	41	6	17	2	19	6	21	28	29	9	5	0	7	0	0	8	5	7	41	1	12	1	2	0	0	2	2	24	6	4	0	6	2	7	0	0	1	0	0	15	0	1	0	0	0	6	0	49	0	1	3	1	0	0	3	1	2	0	0	0	1	0	0	3	0	5	3	0	0	0	0	1	0	0	1	0	0	3	0	11	0	0	0	0	0	6	0	1	0	0	0	0	0	0	1	4	2	0	1	0	22	1	1	0	0	0	4	1	7	10	4	5	4	8	1	0	0	0	0	0	0	0	0	5	0	0	0	0	0	3	0
10101031006	1892	57	9	1	3	0	0	0	10	0	1	10	0	1	0	5	1	0	0	0	0	3	3	0	0	0	0	0	0	0	0	0	0	15	0	0	0	0	8	0	1	0	0	0	0	0	1	0	0	0	6	0	0	0	0	0	0	0	0	0	0	7	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	11	1	1	0	0	0	0	1	0	16	1	1	0	0	0	0	0	0	2	0	0	0	0	0	0	1	0	0	0	0	0	0	10	0	0	0	0	0	0	0	1	0	1	1	0	0	0	0	0	0	1	2	0	1	0	0	1	0	0	0	0	0	1	3	29	1	12	4	3	2	24	21	9	20	2	0	2	8	1	12	4	6	27	2	8	1	0	0	1	2	1	10	2	1	1	5	1	4	0	0	0	0	0	13	0	0	0	0	0	2	2	20	0	0	2	2	0	2	0	1	3	0	2	0	5	0	1	0	1	9	5	1	3	0	1	0	0	0	0	0	1	0	0	3	0	2	0	0	0	3	0	0	0	0	0	0	0	0	1	1	0	0	1	0	26	1	1	0	0	0	2	0	6	1	0	2	0	4	1	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0
10101031007	1991	78	4	0	0	0	0	0	2	0	0	1	0	0	1	0	0	0	0	1	0	2	1	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	1	0	0	2	7	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	3	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	3	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	6	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	1	16	5	3	0	10	4	4	11	0	4	0	0	0	0	0	1	0	0	16	0	2	1	2	0	2	1	0	13	1	2	0	5	1	0	0	0	5	0	2	9	0	0	0	0	0	0	0	15	0	0	0	3	0	0	0	0	1	0	0	0	0	0	0	0	0	4	0	0	0	1	0	0	0	0	0	0	3	4	0	1	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	6	0	1	2	0	0	0	0	2	0	0	2	0	3	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0
10101031008	3176	72	11	0	0	4	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	2	2	0	2	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	3	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	6	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	1	1	0	2	0	1	0	2	0	0	0	0	0	1	0	1	18	2	12	3	8	7	21	13	9	8	9	1	1	0	0	6	2	1	32	0	1	0	0	2	1	0	0	8	0	4	0	3	1	0	2	0	0	0	4	9	0	1	0	0	0	0	0	16	0	0	0	1	0	0	0	0	2	1	0	0	1	0	0	3	0	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	18	0	0	1	0	0	4	0	7	1	2	4	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
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10101061005	2198	85	19	0	4	0	0	0	5	0	0	0	0	0	0	3	0	0	0	0	0	2	4	0	0	0	0	0	0	0	0	0	0	6	0	0	0	1	4	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	2	4	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8	4	2	0	0	0	0	0	0	4	0	1	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	1	0	0	0	15	0	0	0	0	0	0	6	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	3	9	5	0	8	6	0	8	11	4	4	0	0	0	0	0	5	0	0	12	1	1	1	3	0	0	0	0	5	1	5	0	0	2	4	0	0	0	0	0	10	0	0	0	0	0	0	0	20	0	1	1	3	0	2	0	0	1	0	3	1	0	1	0	0	0	2	0	1	1	0	0	0	1	0	4	0	0	0	0	3	1	0	2	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	7	0	1	2	0	0	0	0	1	1	1	2	1	3	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0
10101061006	3208	80	11	0	10	0	0	0	13	0	0	0	0	0	0	4	0	0	0	1	0	1	3	0	0	0	0	0	0	0	0	0	0	9	0	1	0	0	17	0	0	0	0	1	0	1	0	0	0	0	1	0	0	0	0	3	1	0	0	0	0	2	0	0	6	2	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	3	1	1	0	0	2	0	0	3	0	1	0	0	0	1	0	7	0	0	0	1	40	5	1	0	0	4	1	0	0	9	1	2	0	2	1	0	0	0	0	3	0	0	0	0	0	0	0	0	0	1	0	0	46	0	0	0	1	0	0	1	0	0	0	1	0	0	4	1	0	0	1	2	0	6	1	0	0	0	0	0	0	0	0	9	14	6	5	6	11	6	8	33	38	23	2	0	0	1	2	18	7	4	53	1	8	0	3	0	0	4	5	5	3	19	0	14	1	9	0	0	0	0	0	14	0	0	0	3	0	4	0	84	4	1	0	6	1	2	0	0	6	2	3	0	9	0	1	1	0	7	6	1	3	8	1	0	1	2	4	0	2	0	0	4	0	0	1	0	0	2	0	0	0	0	0	0	0	0	2	0	0	0	1	0	49	1	0	6	0	2	1	1	11	0	2	1	6	10	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0
10101061007	679	23	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	0	1	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	2	4	2	1	2	1	5	6	4	1	1	0	3	0	0	0	0	0	8	4	3	0	1	0	0	0	5	1	0	5	0	0	0	0	0	0	0	0	0	6	0	0	0	0	0	0	0	8	0	4	0	3	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	7	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101061008	1726	45	5	0	2	0	0	0	7	1	0	0	0	0	0	0	0	0	0	1	0	5	1	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	12	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	2	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	6	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	3	3	0	0	0	0	0	0	0	0	2	1	0	4	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	11	7	2	4	2	8	5	25	7	7	0	1	0	1	0	4	3	2	22	2	2	0	1	2	0	5	0	5	0	0	0	2	0	7	0	0	1	0	0	5	0	0	0	0	4	1	1	37	3	0	0	1	0	0	0	0	4	0	6	0	0	2	0	4	5	3	2	3	1	1	0	3	0	4	0	0	0	0	0	6	0	0	0	1	0	2	0	0	0	0	0	0	0	0	0	0	0	0	2	0	12	0	3	0	0	0	0	0	1	0	2	2	5	3	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101061009	143	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	1	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	1	0	0	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101061010	1304	77	5	0	1	0	0	0	3	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	2	0	0	0	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	3	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	4	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	2	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	3	1	1	4	3	3	5	0	9	3	1	0	0	0	0	0	3	0	0	11	0	2	1	0	0	0	0	0	4	0	1	0	2	0	0	0	0	0	0	0	5	0	0	0	1	0	0	1	21	0	0	0	0	0	0	0	0	5	0	0	0	0	0	1	0	0	1	0	4	1	0	3	0	0	0	0	0	0	0	0	6	0	0	0	0	0	2	1	0	0	0	1	2	0	0	0	0	0	0	1	0	3	0	0	0	0	0	0	1	0	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062003	129	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	3	3	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	5	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062008	468	12	1	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	0	0	5	6	3	0	0	0	0	0	6	0	0	5	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8	1	0	0	0	0	0	0	0	1	0	0	0	12	1	0	0	4	0	6	0	6	4	2	0	1	0	0	0	0	0	0	5	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	6	0	0	0	0	0	0	0	0	0	0	4	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062013	438	54	2	0	0	0	0	0	0	0	0	0	0	0	0	6	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	8	1	2	0	1	1	0	0	0	1	0	0	0	0	0	0	0	0	1	0	2	0	0	0	0	0	0	0	0	0	0	0	9	0	0	0	0	0	0	0	5	0	0	0	0	0	0	1	0	0	0	0	0	4	4	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	1	6	0	0	1	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062029	41	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062039	64	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

write.table(tabla_P11COMUNA,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P11COMUNA.xlsx")

P12COMUNA Comuna de de nacimiento.

tabla_P12COMUNA <- table(x$clave, x$P12COMUNA, useNA = "no")
#write_xlsx(tabla_P12COMUNA, "tabla_P12COMUNA.xlsx")

a_008 <- head(tabla_P12COMUNA,50)

kbl(a_008) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	98	99	997	1000	1101	1107	1401	1403	1404	2101	2102	2103	2104	2201	2301	2302	3000	3101	3102	3103	3201	3202	3301	3302	3303	3304	4000	4101	4102	4103	4104	4106	4201	4202	4203	4204	4301	4302	4303	4304	4305	5000	5101	5102	5103	5105	5107	5109	5201	5301	5303	5304	5401	5402	5404	5405	5501	5502	5503	5504	5506	5601	5602	5603	5604	5605	5606	5701	5702	5703	5704	5705	5706	5801	5802	5803	5804	6000	6101	6102	6103	6104	6105	6106	6107	6108	6109	6110	6111	6112	6113	6114	6115	6116	6117	6201	6202	6203	6204	6205	6206	6301	6302	6303	6304	6305	6306	6307	6308	6309	6310	7000	7101	7102	7103	7104	7105	7106	7107	7108	7109	7110	7201	7202	7203	7301	7302	7303	7304	7305	7306	7307	7308	7309	7401	7402	7403	7404	7405	7406	7407	7408	8000	8101	8102	8103	8104	8105	8106	8107	8108	8109	8110	8111	8112	8201	8202	8203	8204	8205	8206	8207	8301	8302	8303	8304	8305	8306	8307	8308	8309	8310	8311	8312	8313	8314	9000	9101	9102	9103	9104	9105	9106	9107	9108	9109	9110	9111	9112	9113	9114	9115	9116	9117	9118	9119	9120	9121	9201	9202	9203	9204	9205	9206	9207	9208	9209	9210	9211	10000	10102	10103	10104	10105	10106	10107	10108	10109	10201	10202	10203	10204	10205	10206	10207	10208	10209	10210	10301	10302	10303	10304	10305	10306	10307	10401	10402	10403	10404	11000	11101	11102	11201	11202	11203	11301	11302	11303	11401	11402	12000	12101	12104	12201	12202	12301	12302	12401	13000	13101	13102	13103	13104	13105	13106	13107	13108	13109	13110	13111	13112	13113	13114	13115	13116	13117	13118	13119	13120	13121	13122	13123	13124	13125	13126	13127	13128	13129	13130	13131	13132	13201	13202	13203	13301	13302	13303	13401	13402	13403	13404	13501	13502	13503	13504	13505	13601	13602	13603	13604	13605	14000	14101	14102	14103	14104	14105	14106	14107	14108	14201	14202	14203	14204	15000	15101	15201	15202	16101	16102	16103	16104	16105	16106	16107	16108	16109	16201	16202	16203	16204	16205	16206	16207	16301	16302	16303	16304	16305
10101011001	238	5	5	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	8	0	0	0	0	6	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	1	0	0	1	3	0	0	0	0	0	0	0	2	0	0	1	0	1	0	0	0	18	0	2	0	0	0	0	0	0	3	0	1	2	0	1	0	0	0	0	2	0	2	1	0	0	0	0	0	1	0	0	0	0	1	6	2	0	0	0	0	0	2	3	0	1	0	0	1	0	1	0	0	0	2	0	3	2	1	0	0	0	0	0	0	0	0	6	8	3	9	6	3	2	4	11	12	6	2	0	2	0	0	3	2	1	26	0	4	1	3	0	0	2	0	1	3	0	6	0	4	0	0	0	0	0	0	0	0	4	1	0	0	0	0	2	0	43	0	0	0	1	1	1	2	1	1	0	0	1	1	0	0	0	1	1	5	1	0	0	0	0	0	2	1	0	5	0	1	1	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	16	0	0	0	0	0	0	2	3	0	2	1	0	3	0	0	6	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101011002	1526	27	37	0	5	0	0	0	0	5	1	0	0	1	1	1	0	4	1	1	0	0	3	0	0	1	0	0	2	0	1	0	2	0	1	1	0	0	1	0	0	0	27	0	1	0	0	21	0	1	0	0	1	0	0	0	2	1	2	0	0	5	0	0	0	0	0	4	0	1	1	1	0	9	1	0	0	0	12	0	1	1	0	0	0	0	0	0	0	0	0	0	1	0	3	3	0	1	0	0	0	4	0	0	0	0	0	0	0	0	0	0	6	1	0	0	1	0	0	0	1	0	1	0	0	5	0	0	0	0	0	0	1	0	5	1	0	3	0	1	1	0	0	22	2	0	0	1	1	2	0	1	21	1	0	1	2	1	0	3	0	2	9	2	0	1	2	2	0	0	0	0	1	2	0	0	0	24	1	2	0	0	0	2	3	2	0	1	0	0	5	1	1	0	1	2	1	0	5	0	2	1	0	0	0	1	0	0	1	29	34	19	44	23	30	10	37	43	45	69	8	1	11	7	1	20	12	25	88	7	6	1	7	1	2	7	4	20	6	0	14	0	12	2	0	0	0	0	2	0	2	50	1	1	0	2	0	5	1	138	1	1	4	3	1	1	7	3	2	1	0	0	1	0	0	0	1	5	2	1	2	7	1	0	7	3	1	0	8	1	2	4	0	0	2	2	0	8	1	0	0	0	1	0	0	0	2	0	0	0	1	1	45	1	0	4	0	4	1	6	12	4	4	10	0	5	0	0	18	1	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0	0	0	0	0
10101021001	2393	41	54	0	1	0	0	0	0	3	0	0	0	3	0	1	0	3	0	0	0	0	0	0	0	0	0	2	2	0	0	0	0	1	0	0	2	0	0	0	0	0	28	1	0	1	0	9	0	3	0	0	0	0	0	1	4	0	0	0	0	7	0	0	0	0	0	1	0	0	0	0	2	4	2	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	1	0	0	0	0	0	2	0	0	0	0	0	1	0	0	1	0	4	1	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	2	0	0	1	1	1	1	1	2	16	1	0	0	0	0	1	0	1	3	4	1	1	0	0	0	0	3	0	7	0	1	0	0	0	0	0	0	0	1	1	0	0	3	39	3	3	0	0	0	1	0	5	0	1	0	0	1	0	4	5	1	0	2	0	1	2	1	0	1	0	3	0	1	0	4	23	110	35	48	36	60	18	92	60	48	50	1	2	7	3	3	8	12	13	93	11	32	2	14	3	3	13	6	22	2	0	19	1	15	3	2	0	0	0	1	1	1	22	1	0	0	0	0	1	0	108	0	0	6	2	5	1	5	3	5	2	0	2	2	0	2	0	2	3	0	1	2	5	2	0	8	6	1	3	7	1	0	7	0	1	1	1	0	5	0	0	0	10	0	0	0	0	0	0	0	0	0	1	45	4	2	5	1	1	2	5	10	6	8	20	0	6	0	0	10	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	1	0	0	0	0
10101021002	480	11	14	0	3	0	0	0	0	2	0	0	1	3	0	0	0	1	2	0	0	0	1	0	0	0	1	5	1	0	0	0	1	0	0	1	1	0	0	0	0	0	12	0	0	0	0	4	0	1	2	0	0	0	0	0	2	1	0	0	0	2	0	2	1	0	0	1	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	1	1	4	0	1	0	0	0	0	0	0	1	0	4	2	0	0	0	0	1	1	1	0	0	0	0	2	0	0	1	0	0	0	0	0	0	0	1	4	1	2	0	0	5	15	2	1	0	0	4	1	0	0	8	1	1	0	0	0	0	0	0	0	10	0	2	0	0	0	0	0	0	0	0	0	0	0	0	14	0	0	0	0	0	1	0	2	0	1	0	1	3	1	0	0	1	0	1	0	6	0	1	0	1	0	0	0	0	1	1	5	19	9	8	13	13	6	22	14	11	25	3	2	3	3	4	9	1	1	31	1	3	0	1	0	1	5	2	7	0	0	6	0	3	0	0	0	0	0	1	0	0	12	0	0	0	0	0	6	0	59	2	2	4	1	4	0	4	1	5	5	0	0	7	0	0	1	2	2	0	0	0	4	1	2	0	1	0	2	7	0	0	3	0	0	0	0	0	3	0	0	0	2	0	0	0	0	2	0	0	1	1	0	20	1	2	1	0	2	0	1	5	1	3	6	0	1	0	0	5	2	0	0	2	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0
10101021003	1087	32	39	0	8	1	1	0	0	2	1	0	0	1	0	0	0	1	0	1	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	17	0	0	0	2	9	0	3	1	0	0	0	0	0	0	2	0	0	0	1	0	0	0	0	0	2	0	0	0	0	2	5	0	0	1	0	13	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	8	0	0	0	0	0	2	0	0	1	0	5	0	0	0	0	0	0	0	0	0	0	0	1	1	1	0	0	1	0	0	0	0	1	0	0	1	0	1	0	0	0	22	1	2	0	0	3	0	0	0	16	2	0	0	0	0	0	2	0	0	12	1	1	1	0	3	0	0	0	0	1	0	0	0	0	24	2	0	0	0	0	0	4	1	0	0	0	1	1	0	0	1	4	0	3	0	5	1	0	3	1	0	1	0	1	0	3	31	50	11	27	14	26	11	37	22	30	53	10	9	7	3	13	10	20	16	100	4	20	4	8	3	4	10	2	8	5	0	11	0	9	3	2	0	0	0	2	1	0	18	0	0	0	2	0	5	2	100	0	2	3	6	2	0	1	3	3	1	1	1	2	0	1	1	3	6	3	1	3	4	4	2	2	2	0	1	10	1	0	4	0	0	1	0	0	5	0	0	0	2	0	0	0	0	0	0	0	0	0	1	34	1	1	2	0	1	9	3	20	3	3	12	0	1	0	0	8	1	0	1	0	0	0	0	1	2	0	2	0	0	0	0	1	0	0	0	0
10101021004	2020	41	61	0	3	0	0	0	1	1	0	0	0	2	0	0	0	0	1	0	1	0	0	1	0	0	0	1	1	0	0	0	0	0	0	0	2	1	1	0	0	0	22	0	0	0	3	8	0	1	0	0	0	0	1	0	4	0	0	0	0	2	0	0	0	0	0	1	1	2	0	0	0	2	1	0	1	0	9	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	5	2	0	0	1	0	1	0	0	0	1	0	0	3	1	0	2	0	0	0	0	0	1	0	0	4	0	1	0	0	0	19	1	0	1	0	1	2	0	1	22	2	1	3	3	0	0	0	1	1	2	0	1	1	0	0	1	0	0	0	0	0	0	0	1	21	2	0	1	2	0	0	2	3	1	3	1	0	1	4	0	1	4	1	5	0	2	3	0	0	0	1	1	1	0	1	0	13	84	34	26	20	28	12	54	49	32	41	9	3	15	6	4	12	29	10	73	18	21	0	10	5	2	14	1	54	5	1	29	2	13	2	5	2	0	0	2	1	0	26	0	0	0	0	0	3	0	102	0	1	6	4	0	1	2	1	1	3	0	1	1	0	0	1	0	3	2	0	5	2	1	0	3	1	1	0	4	0	0	2	0	0	0	0	0	7	4	0	2	1	0	0	0	0	0	0	1	0	0	0	39	1	2	2	1	4	6	2	15	2	7	19	0	0	0	0	8	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	1	0	0	0	0
10101021005	1266	27	51	0	6	0	0	0	0	12	0	0	0	2	0	0	0	1	2	0	0	0	1	0	0	0	0	4	9	0	0	0	0	0	1	0	3	0	0	0	1	0	23	0	0	0	4	31	1	4	0	0	2	0	2	0	1	2	0	1	0	3	1	0	1	0	0	1	0	1	0	0	0	6	4	1	3	0	6	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	13	0	0	0	5	0	0	0	1	0	1	0	0	6	0	0	2	0	0	0	0	0	3	0	1	1	0	0	0	0	2	41	7	1	0	0	1	2	2	0	31	7	0	0	0	0	0	0	2	0	11	0	3	1	1	2	2	0	1	0	0	0	0	0	1	24	1	2	0	2	1	3	0	3	0	2	0	0	0	0	0	0	1	1	3	0	3	1	4	0	2	0	1	1	0	1	0	14	37	21	17	22	36	16	31	52	9	24	5	0	6	1	2	11	6	4	64	6	16	0	6	1	0	12	0	32	2	1	19	1	15	3	0	0	0	0	2	0	0	33	1	0	0	0	0	2	0	122	0	3	1	0	2	0	1	3	5	2	2	3	5	0	0	0	3	7	9	1	1	8	2	2	5	5	0	0	6	3	1	4	0	0	0	1	0	5	1	0	0	2	0	0	0	0	2	0	0	0	0	0	41	4	3	3	0	1	6	7	22	0	4	15	0	7	1	0	5	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1
10101031001	2386	117	95	0	1	0	0	0	0	9	0	0	0	3	0	0	0	1	0	0	0	0	0	0	0	1	0	1	7	1	0	0	0	0	0	0	1	0	1	0	0	0	10	1	0	0	0	11	0	0	0	0	1	0	0	0	0	1	0	0	0	4	0	0	0	0	0	2	0	0	0	0	0	2	1	0	0	0	5	0	0	0	0	0	3	1	0	0	0	0	3	0	0	0	1	0	0	0	0	1	0	3	0	2	0	0	0	0	0	0	1	0	9	2	0	0	2	0	0	0	1	0	3	0	0	5	0	0	2	0	0	0	1	0	4	0	0	1	0	2	1	0	1	45	3	1	0	1	2	1	0	0	17	1	0	1	0	6	1	1	4	0	6	1	0	1	2	1	0	1	0	1	0	1	1	0	0	31	3	3	0	4	1	4	3	2	0	1	1	1	3	1	2	0	2	2	10	0	3	0	2	0	0	1	0	0	0	2	0	80	103	30	83	33	135	49	159	87	34	40	3	5	11	5	1	21	22	28	135	15	42	6	24	2	4	12	3	25	3	0	21	0	27	1	0	0	0	0	2	0	1	32	1	0	0	2	0	6	1	122	0	0	1	0	0	0	0	0	2	5	0	2	5	0	0	0	1	3	6	0	1	5	2	0	2	1	0	3	7	2	0	6	0	0	1	0	0	8	0	0	0	5	0	0	0	0	2	0	1	0	1	2	47	0	1	4	3	3	3	3	22	4	13	23	0	3	0	0	10	0	0	1	0	1	0	1	0	0	0	1	0	0	1	0	2	1	1	0	0
10101031002	2501	36	77	0	5	1	0	1	0	2	0	0	0	1	1	2	0	1	0	0	0	0	1	0	0	1	0	2	2	0	0	0	1	0	1	1	1	0	0	1	0	0	26	0	0	1	1	11	0	2	0	0	0	1	0	0	2	0	1	0	0	5	1	0	0	0	0	5	0	0	0	0	0	1	1	0	8	0	13	0	0	0	1	0	2	4	1	0	0	2	0	1	1	0	2	0	0	0	0	0	1	1	0	1	0	0	0	0	1	0	0	0	7	1	1	1	1	0	0	0	0	0	1	2	0	8	1	0	1	0	0	0	1	0	6	0	1	2	0	0	0	1	2	36	5	0	0	2	8	2	0	0	23	11	2	2	1	1	0	1	2	1	19	0	0	1	1	3	0	0	0	0	0	2	1	0	6	49	2	1	1	1	0	1	2	7	0	3	1	0	6	2	1	3	2	2	11	0	5	1	2	3	0	1	2	1	1	5	2	17	107	32	99	27	128	39	124	83	43	55	6	5	7	6	4	13	18	11	156	11	38	5	28	2	2	29	5	32	6	0	31	0	24	3	5	1	0	0	6	0	0	43	0	0	0	0	0	7	1	148	1	0	5	3	4	1	2	3	5	2	0	1	4	0	1	0	1	7	5	1	1	4	1	0	10	2	1	3	5	1	0	6	0	0	0	0	1	11	3	0	2	1	1	1	0	0	3	2	0	0	0	0	48	4	3	6	0	1	13	17	46	6	9	36	0	3	0	0	9	1	1	1	0	0	0	0	0	1	0	0	0	0	1	0	1	0	0	0	0
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10101061007	420	16	11	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	3	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	1	2	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	14	0	0	0	0	3	3	0	0	2	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	2	12	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	3	0	1	0	1	0	0	0	0	0	0	1	0	0	0	1	19	11	12	15	22	3	14	22	7	9	1	1	3	0	0	1	3	3	29	5	7	2	2	5	0	2	5	3	2	0	6	0	1	0	0	0	0	0	0	0	0	9	0	0	0	0	0	0	2	23	0	2	0	3	0	0	1	1	1	0	0	0	0	0	0	0	0	0	3	0	0	1	2	2	0	0	0	0	1	1	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	7	0	0	2	0	0	3	0	6	1	2	2	0	1	0	0	2	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0
10101061008	1013	39	17	0	3	0	0	0	0	12	1	0	0	2	0	0	0	1	0	0	0	0	1	0	0	2	0	3	2	0	0	0	1	0	0	0	0	1	0	0	0	0	22	0	0	0	1	21	0	0	0	0	0	0	0	0	2	0	0	0	1	4	0	0	0	0	0	1	0	0	0	0	0	2	0	0	2	1	5	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	6	0	0	0	1	0	0	0	0	0	0	6	1	0	0	0	0	1	2	0	0	1	0	0	4	0	0	0	0	0	0	1	0	4	0	1	2	0	0	0	0	1	16	0	1	2	0	0	1	0	1	9	2	0	3	1	0	0	1	0	0	10	0	1	0	2	2	0	0	0	0	0	0	0	0	0	38	2	0	1	2	0	0	2	3	0	0	0	0	2	2	4	2	1	0	4	0	1	1	0	0	1	0	1	3	0	2	2	6	28	10	45	14	24	17	26	41	16	39	2	1	0	3	2	7	2	8	75	3	17	3	4	1	1	12	2	6	0	0	16	0	17	0	0	0	0	0	2	0	0	23	0	0	0	0	1	6	2	97	3	6	3	0	1	0	5	0	8	0	5	3	1	0	1	2	4	1	2	1	2	5	2	3	4	8	1	2	5	1	0	5	0	0	1	0	0	7	0	0	0	1	0	0	0	0	0	0	0	0	4	0	46	0	5	1	0	2	1	6	13	0	3	10	0	11	1	0	9	2	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	1	0	1	0
10101061009	92	0	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	6	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	3	4	2	1	1	2	1	3	0	1	0	0	2	0	0	0	0	0	4	1	1	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	2	2	0	0	0	5	0	0	0	1	0	0	1	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0
10101061010	950	54	19	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	0	0	0	0	8	0	0	0	0	0	0	0	0	2	1	0	0	0	1	0	0	0	0	0	0	1	3	0	0	0	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	2	0	0	0	0	0	0	0	0	0	0	3	0	0	1	0	1	0	0	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	3	0	0	6	1	0	1	0	0	0	0	1	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	2	3	1	0	1	1	2	2	0	2	0	0	0	1	0	1	1	0	3	6	2	0	0	0	0	0	1	0	0	0	2	3	0	6	12	4	31	22	22	22	8	21	6	3	0	0	0	1	3	2	0	5	41	5	27	2	5	1	1	3	1	7	2	0	6	0	2	0	1	0	0	0	0	0	0	8	0	0	0	0	0	0	1	57	0	1	1	1	1	0	0	0	7	1	0	1	0	0	3	0	0	5	2	1	5	1	1	0	3	0	0	3	2	1	0	2	0	0	0	0	0	7	0	0	0	0	0	1	0	0	0	0	0	0	1	0	17	1	1	0	0	1	0	4	7	1	1	5	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062003	86	3	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	4	1	1	5	1	0	0	2	0	0	2	0	0	0	0	0	0	3	10	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	1	0	0	4	1	0	4	0	0	0	1	0	1	1	0	1	2	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	3	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062008	269	3	3	0	2	0	0	0	0	5	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	3	3	0	0	0	0	0	0	0	1	0	0	1	0	0	2	0	0	0	1	4	0	0	0	0	0	1	0	0	2	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	1	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	1	0	0	0	0	0	0	0	0	2	0	1	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	5	0	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	4	0	0	0	1	0	0	0	0	0	0	0	0	0	1	6	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	2	3	3	1	4	6	3	2	11	4	10	2	1	0	0	0	3	2	0	22	2	6	0	1	0	0	4	0	1	1	0	2	0	6	0	0	0	0	0	0	0	0	5	0	0	0	1	0	0	0	53	0	0	1	0	1	0	1	1	2	0	0	0	7	0	0	0	2	2	7	0	2	4	3	0	1	2	0	0	2	1	4	0	0	0	0	0	0	1	2	0	0	0	0	0	0	0	0	0	0	0	0	0	15	1	0	1	1	0	0	1	8	0	0	4	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0
10101062013	276	20	12	0	2	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	2	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	6	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	0	2	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	14	0	0	0	0	1	0	0	0	4	0	0	0	0	1	0	0	0	0	3	0	0	3	1	0	0	0	0	0	0	0	0	0	0	9	0	0	0	0	0	0	0	1	0	0	0	0	0	1	1	0	0	0	3	0	0	0	2	0	0	0	1	0	0	1	2	2	1	1	5	3	1	0	3	20	3	5	0	3	4	1	0	1	2	2	9	2	1	0	3	0	0	1	0	4	0	0	3	0	2	1	0	0	0	0	0	0	0	10	0	0	0	0	0	0	0	46	0	1	0	0	0	0	2	0	1	0	0	1	1	2	0	0	0	0	0	0	1	0	0	0	0	0	0	0	2	5	0	3	0	0	0	0	0	0	0	0	1	0	0	4	0	0	0	0	0	0	0	0	6	0	0	1	0	0	0	3	7	0	0	2	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0
10101062029	24	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	2	1	0	1	0	0	0	0	0	0	0	0	0	0	1	0	3	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
10101062039	55	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	1	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

write.table(tabla_P12COMUNA ,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P12COMUNA .xlsx")

P10PAIS País de residencia habitual.

tabla_P10PAIS <- table(x$clave, x$P10PAIS, useNA = "no")

#write_xlsx(tabla_P10PAIS, "tabla_P10PAIS.xlsx")

a_010 <- head(tabla_P10PAIS,50)

kbl(a_010) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	32	36	76	100	124	156	170	218	250	276	380	392	484	554	578	604	608	724	752	756	826	840	858	862	997	998	999
10101011001	69	1	2	0	0	3	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	2	0	2	498	6
10101011002	23	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	2894	23
10101021001	4	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	1	0	0	0	0	0	0	3911	35
10101021002	19	2	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1080	5
10101021003	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	2	0	4	0	0	0	0	0	0	0	2264	22
10101021004	4	0	0	0	0	0	0	1	0	0	0	0	0	0	0	2	17	0	0	0	0	0	0	0	2	3331	34
10101021005	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2531	32
10101031001	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	4455	72
10101031002	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	4711	26
10101031003	2	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4071	33
10101031004	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2835	19
10101031005	4	0	0	0	0	0	1	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	5624	56
10101031006	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2415	45
10101031007	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2264	27
10101031008	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	3560	22
10101031009	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4400	35
10101031010	2	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	3531	30
10101031011	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2697	57
10101031012	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1818	30
10101031013	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3855	88
10101031014	2	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2244	17
10101031015	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1919	11
10101031016	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3049	22
10101031017	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3848	36
10101032002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	127	2
10101032011	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	419	7
10101032019	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	824	5
10101041001	1	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	4292	46
10101041002	2	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2140	26
10101041003	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	2	0	5131	65
10101042010	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	2
10101051001	5	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	2413	41
10101051002	5	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1893	14
10101051003	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3212	60
10101051004	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3544	87
10101061001	4	0	0	0	0	1	0	4	0	0	2	0	0	0	0	3	0	1	0	0	0	0	0	1	0	6724	47
10101061002	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2702	25
10101061003	2	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	3619	46
10101061004	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2948	43
10101061005	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2559	12
10101061006	11	0	0	0	0	0	3	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	4077	37
10101061007	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	810	7
10101061008	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2095	13
10101061009	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	168	0
10101061010	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1522	21
10101062003	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	155	3
10101062008	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	578	1
10101062013	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	561	9
10101062029	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	46	1
10101062039	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	67	0

write.table(tabla_P10PAIS ,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P10PAIS.xlsx")

P11PAIS País de residencia hace 5 años.

tabla_P11PAIS <- table(x$clave, x$P11PAIS, useNA = "no")
#write_xlsx(tabla_P11PAIS, "tabla_P11PAIS.xlsx")

a_011 <- head(tabla_P11PAIS,50)

kbl(a_011) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	29	36	40	51	56	76	100	124	156	188	192	208	214	222	246	250	276	300	320	332	340	376	380	392	410	484	528	554	578	591	600	608	620	643	710	724	752	756	760	764	792	804	826	840	858	862	997	998	999
10101011001	0	1	0	0	0	2	0	0	3	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	1	0	0	4	0	0	0	0	0	2	6	0	551	9
10101011002	0	3	0	0	0	1	0	1	1	0	0	0	0	0	0	2	1	0	0	2	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	6	0	0	0	0	2	1	0	3	0	14	0	2843	59
10101021001	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	1	1	0	0	0	0	0	0	0	0	2	1	0	0	0	0	0	0	1	0	1	0	3871	71
10101021002	0	2	0	0	0	0	0	2	7	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	1	0	0	0	1082	8
10101021003	0	0	0	0	0	1	0	0	0	0	1	0	4	0	0	3	0	0	0	8	0	0	0	0	0	1	0	3	0	0	0	0	0	0	0	5	0	0	0	0	2	0	0	2	0	14	0	2198	52
10101021004	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	0	8	0	0	0	0	0	0	0	0	0	0	0	18	0	0	0	1	0	0	0	0	0	0	0	0	2	14	1	3261	83
10101021005	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	1	0	0	0	0	0	0	4	0	0	0	0	0	0	0	2	0	7	0	2455	91
10101031001	0	0	0	0	0	3	0	0	0	0	0	1	1	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	7	1	4386	127
10101031002	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	2	0	1	0	4634	98
10101031003	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3956	144
10101031004	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2722	132
10101031005	0	0	0	0	0	1	0	1	0	0	0	0	2	0	0	2	1	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	7	0	0	0	0	0	0	0	2	1	0	0	5571	100
10101031006	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	5	1	0	0	0	0	0	0	1	0	1	0	2392	57
10101031007	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2212	78
10101031008	0	0	0	0	1	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	4	0	1	0	3502	72
10101031009	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	4356	79
10101031010	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	3473	92
10101031011	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2614	142
10101031012	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1798	48
10101031013	0	2	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	3824	116
10101031014	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	0	4	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	0	2200	53
10101031015	0	0	0	0	0	0	0	3	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	3	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1877	42
10101031016	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	1	0	0	0	0	0	0	0	0	8	0	2986	69
10101031017	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	7	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	3839	37
10101032002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	121	8
10101032011	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	414	12
10101032019	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	787	42
10101041001	0	0	0	0	1	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	2	0	4233	100
10101041002	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	2066	99
10101041003	0	0	0	0	0	2	0	1	0	3	0	0	0	0	0	1	0	0	0	2	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	1	2	8	1	5095	83
10101042010	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	1
10101051001	0	0	0	0	1	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	4	0	0	1	1	0	0	1	6	0	1	0	2300	144
10101051002	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	4	0	1793	111
10101051003	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	3188	81
10101051004	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	2	2	0	0	0	0	0	1	2	0	0	0	0	1	0	0	0	0	0	0	6	0	0	0	0	0	0	0	4	1	15	0	3481	117
10101061001	0	0	1	0	0	12	0	1	1	1	6	0	1	0	0	0	0	0	0	2	0	0	3	0	0	1	0	1	0	0	1	0	0	0	1	16	0	0	0	0	0	0	1	2	1	16	1	6646	72
10101061002	0	4	0	0	0	1	0	0	0	1	0	0	0	0	0	3	1	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	6	0	0	0	0	0	0	1	2	0	2	0	2676	29
10101061003	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	3	0	3604	54
10101061004	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	0	2897	94
10101061005	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	3	0	10	0	2471	85
10101061006	1	0	0	1	1	1	0	1	0	0	1	0	0	0	0	0	8	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	4	4	15	0	4009	80
10101061007	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	793	23
10101061008	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	2061	45
10101061009	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	167	1
10101061010	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1465	77
10101062003	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	153	5
10101062008	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	563	12
10101062013	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	516	54
10101062029	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	46	1
10101062039	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	66	1

write.table(tabla_P11PAIS,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P11PAIS.xlsx")

P12PAIS País de nacimiento.

tabla_P12PAIS <- table(x$clave, x$P12PAIS, useNA = "no")
#write_xlsx(tabla_P12PAIS, "tabla_P12PAIS.xlsx")

a_012 <- head(tabla_P12PAIS,50)

kbl(a_012) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	2	5	12	36	40	51	56	76	100	124	150	156	188	192	208	214	222	250	276	300	320	332	340	356	364	376	380	392	410	484	504	528	558	578	591	600	608	616	620	630	643	688	710	724	752	756	760	764	792	804	818	826	840	858	862	997	998	999
10101011001	0	0	0	0	0	0	0	2	0	0	0	4	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	6	0	0	4	0	0	0	0	0	0	1	6	0	552	5
10101011002	0	0	0	0	0	0	0	1	0	0	0	4	0	0	0	0	0	2	1	0	0	2	0	0	0	0	0	1	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	2	0	0	3	0	2	1	0	0	1	0	13	0	2879	27
10101021001	0	0	0	0	0	0	0	2	0	0	0	2	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	2	0	3901	41
10101021002	0	0	0	2	0	0	0	0	0	2	0	14	0	1	0	1	0	0	2	0	0	0	0	1	0	0	1	2	0	1	1	1	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	0	0	0	0	2	1	0	2	0	1059	11
10101021003	0	0	0	0	0	0	0	1	0	0	0	0	0	3	0	1	0	2	0	0	0	9	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	2	0	0	0	0	2	0	0	0	1	0	15	1	2223	32
10101021004	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	1	1	0	2	0	0	10	0	0	0	0	0	0	0	0	0	0	0	0	0	0	18	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	1	14	1	3298	41
10101021005	0	0	0	0	0	0	1	4	0	0	0	0	1	0	0	0	0	0	5	0	0	0	0	0	0	0	0	0	0	3	0	1	0	0	0	1	0	0	0	0	0	0	0	5	0	0	5	0	0	0	0	1	1	1	8	0	2500	27
10101031001	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	1	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	0	0	0	8	1	4393	117
10101031002	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	2	0	2	0	4690	36
10101031003	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	4037	64
10101031004	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	2814	39
10101031005	0	0	1	1	0	0	0	2	0	1	0	0	0	0	0	3	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	4	0	0	0	0	0	0	0	0	0	2	0	0	5591	80
10101031006	0	0	0	1	0	0	0	1	0	0	1	0	0	0	1	0	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	1	0	2400	50
10101031007	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	2264	24
10101031008	0	0	0	0	0	0	1	3	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	1	0	2	0	3520	52
10101031009	0	1	0	0	0	0	0	0	0	0	1	0	0	1	0	3	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	1	4370	56
10101031010	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3501	62
10101031011	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2652	103
10101031012	0	0	0	0	0	0	0	1	0	1	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	1	0	1814	27
10101031013	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	3833	110
10101031014	0	0	0	0	0	0	0	3	0	1	0	0	0	0	0	0	1	0	3	0	0	0	0	0	0	0	0	0	0	4	0	1	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	2	0	2232	16
10101031015	0	0	0	0	0	0	0	0	0	0	0	0	0	2	1	0	0	0	0	0	0	0	0	2	1	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	3	0	0	1899	18
10101031016	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	4	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	1	1	1	0	0	0	0	0	0	0	0	10	0	3021	29
10101031017	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	7	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3848	27
10101032002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	128	1
10101032011	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	420	5
10101032019	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	817	12
10101041001	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	4	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	4291	39
10101041002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	2122	45
10101041003	0	0	0	0	0	0	0	3	0	1	0	0	4	1	0	0	1	2	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	1	0	0	0	3	1	0	0	0	0	0	0	1	2	4	12	0	5090	74
10101042010	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	1
10101051001	0	0	0	0	0	0	0	3	1	0	1	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	1	1	0	2	0	0	0	0	0	0	0	0	0	0	0	0	1	8	0	0	2	1	0	1	0	1	0	0	1	0	2356	79
10101051002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	5	0	1888	16
10101051003	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	3181	87
10101051004	0	0	0	1	0	0	0	2	0	0	0	0	0	0	0	1	0	2	2	0	0	0	0	0	0	0	0	3	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	6	0	0	0	0	0	0	0	0	4	2	11	0	3507	90
10101061001	1	0	0	0	0	0	1	15	0	1	0	1	0	11	0	1	0	1	1	1	0	2	1	0	0	0	4	0	0	0	0	0	3	1	1	3	0	0	0	0	0	1	0	6	0	0	1	0	0	0	0	0	5	7	26	1	6640	51
10101061002	0	0	0	0	1	0	1	4	0	0	0	0	0	3	0	0	1	0	8	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	2	4	2	1	2	0	0	0	0	1	6	0	2	0	2668	21
10101061003	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	1	0	0	3	1	3607	50
10101061004	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	2	0	0	0	0	0	0	0	1	0	1	0	2936	50
10101061005	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	1	1	0	9	2	2515	38
10101061006	0	0	0	1	0	1	0	1	0	0	0	0	0	3	0	1	0	0	3	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	3	0	0	3	0	0	1	0	0	0	0	0	5	1	18	1	4047	40
10101061007	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	801	16
10101061008	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	2	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	2062	39
10101061009	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	168	0
10101061010	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1486	54
10101062003	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	154	3
10101062008	1	0	0	0	0	0	0	2	1	0	0	3	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	1	0	565	3
10101062013	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	3	0	0	0	0	0	0	0	2	0	542	20
10101062029	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	46	1
10101062039	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	67	0

write.table(tabla_P12PAIS,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P12PAIS.xlsx")

P11 Residencia hace 5 años.

tabla_P11 <- table(x$clave, x$P11, useNA = "no")

colnames(tabla_P11) <- c("Aún no nacía","En esta comuna","En otra comuna","Perú","Argentina","Bolivia","Ecuador","Colombia","Otro","Missing")

#write_xlsx(tabla_P11, "tabla_P11.xlsx")

a_111 <- head(tabla_P11,50)

kbl(a_111) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Aún no nacía	En esta comuna	En otra comuna	Perú	Argentina	Bolivia	Ecuador	Colombia	Otro	Missing
10101011001	16	286	178	0	70	0	1	0	24	9
10101011002	141	2077	592	0	29	0	0	4	39	59
10101021001	198	3121	506	5	9	0	0	32	11	71
10101021002	29	729	286	6	17	0	2	13	17	8
10101021003	91	1559	495	8	4	0	31	10	44	52
10101021004	191	2560	452	13	9	2	7	27	47	83
10101021005	152	1834	445	7	4	0	5	8	18	91
10101031001	229	3526	609	2	5	1	0	14	17	127
10101031002	318	3668	628	2	14	0	3	1	8	98
10101031003	273	3335	336	0	4	0	0	8	7	144
10101031004	168	2220	318	1	5	0	2	8	2	132
10101031005	553	4227	762	1	12	0	0	16	19	100
10101031006	211	1669	511	0	1	0	0	0	11	57
10101031007	142	1843	223	0	1	0	0	3	2	78
10101031008	223	2927	337	5	3	0	2	5	11	72
10101031009	305	3517	522	0	9	0	0	3	1	79
10101031010	264	2923	280	0	4	0	0	2	1	92
10101031011	177	2225	203	2	4	0	0	3	1	142
10101031012	105	1507	183	1	2	0	0	0	3	48
10101031013	300	3147	357	3	14	0	0	3	5	116
10101031014	139	1785	268	0	3	1	1	3	12	53
10101031015	148	1479	233	3	3	1	0	10	11	42
10101031016	236	2367	368	6	2	0	0	7	16	69
10101031017	308	2533	985	2	4	1	0	6	9	37
10101032002	5	110	6	0	0	0	0	0	0	8
10101032011	19	359	32	0	1	0	1	2	0	12
10101032019	58	687	42	0	0	0	0	0	0	42
10101041001	268	3489	460	0	6	0	6	4	9	100
10101041002	125	1699	238	0	3	0	1	0	4	99
10101041003	415	3507	1143	2	14	0	2	12	24	83
10101042010	0	3	1	0	1	0	0	0	0	1
10101051001	102	1696	490	1	6	0	0	5	19	144
10101051002	105	1383	297	0	8	0	0	0	9	111
10101051003	187	2715	271	0	6	0	0	9	3	81
10101051004	156	2464	838	2	7	0	2	12	35	117
10101061001	619	4423	1560	4	13	1	9	17	69	72
10101061002	175	1821	665	0	3	2	0	10	24	29
10101061003	204	2768	616	1	7	1	0	7	10	54
10101061004	151	2122	615	0	7	0	0	2	4	94
10101061005	156	2020	288	0	3	0	1	3	15	85
10101061006	235	2894	842	3	15	0	3	17	41	80
10101061007	69	606	115	0	3	0	0	0	1	23
10101061008	240	1479	338	0	2	1	0	1	3	45
10101061009	16	127	24	0	0	0	0	0	0	1
10101061010	111	1183	162	1	8	0	0	0	1	77
10101062003	15	114	24	0	0	0	0	0	0	5
10101062008	38	422	101	0	0	0	0	2	6	12
10101062013	37	396	79	0	2	0	1	1	1	54
10101062029	1	40	5	0	0	0	0	0	0	1
10101062039	4	60	2	0	0	0	0	0	0	1

write.table(tabla_P11,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P11.xlsx")

P12 Lugar de nacimiento.

tabla_P12 <- table(x$clave, x$P12, useNA = "no")

colnames(tabla_P12) <- c("En esta comuna","En otra comuna","Perú","Argentina","Bolivia","Ecuador","Colombia","Otro","Missing")

#write_xlsx(tabla_P12, "tabla_P12.xlsx")

a_112 <- head(tabla_P12,50)

kbl(a_112) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	En esta comuna	En otra comuna	Perú	Argentina	Bolivia	Ecuador	Colombia	Otro	Missing
10101011001	137	341	0	71	0	1	2	27	5
10101011002	1443	1388	6	36	0	0	6	35	27
10101021001	2295	1519	4	26	0	1	56	11	41
10101021002	396	616	8	23	1	3	12	37	11
10101021003	977	1175	13	7	0	34	17	39	32
10101021004	1861	1330	18	24	2	15	48	52	41
10101021005	1189	1271	7	14	0	10	9	37	27
10101031001	2301	2027	8	39	1	0	17	20	117
10101031002	2438	2203	2	39	0	5	3	14	36
10101031003	2612	1388	2	23	0	1	11	6	64
10101031004	1653	1122	3	21	0	3	12	3	39
10101031005	2879	2647	2	38	0	3	22	19	80
10101031006	1254	1118	2	22	0	0	4	10	50
10101031007	1245	1004	0	11	0	0	4	4	24
10101031008	1907	1586	4	16	0	2	5	13	52
10101031009	2530	1806	1	25	0	4	4	10	56
10101031010	2236	1235	0	24	1	1	4	3	62
10101031011	1674	956	3	17	0	0	2	2	103
10101031012	894	907	0	10	0	0	3	8	27
10101031013	2341	1457	6	21	0	1	7	2	110
10101031014	1179	1034	0	14	0	1	4	17	16
10101031015	906	957	8	10	0	1	17	13	18
10101031016	1547	1426	12	24	0	3	9	21	29
10101031017	1649	2151	5	31	0	3	9	10	27
10101032002	96	30	0	2	0	0	0	0	1
10101032011	297	114	0	8	0	0	1	1	5
10101032019	677	140	0	0	0	0	0	0	12
10101041001	2475	1767	4	30	0	7	8	12	39
10101041002	1172	932	1	12	2	1	2	2	45
10101041003	2080	2941	5	26	1	17	20	38	74
10101042010	1	4	0	0	0	0	0	0	1
10101051001	1041	1290	3	17	0	0	5	28	79
10101051002	997	878	1	12	0	0	0	9	16
10101051003	2014	1135	0	19	0	2	11	4	87
10101051004	1520	1935	1	25	0	2	24	36	90
10101061001	2524	3998	9	42	1	28	38	96	51
10101061002	1224	1408	2	12	3	3	16	40	21
10101061003	1907	1662	2	22	1	1	12	11	50
10101061004	1566	1343	1	22	0	1	3	9	50
10101061005	1314	1175	2	14	1	5	4	18	38
10101061006	1595	2382	4	38	1	9	18	43	40
10101061007	409	381	0	10	0	0	1	0	16
10101061008	984	1057	0	18	2	1	0	8	39
10101061009	90	76	0	2	0	0	0	0	0
10101061010	936	539	1	10	0	0	0	3	54
10101062003	85	69	0	0	0	0	0	1	3
10101062008	251	309	0	3	0	0	2	13	3
10101062013	265	275	0	0	0	1	1	9	20
10101062029	24	22	0	0	0	0	0	0	1
10101062039	55	12	0	0	0	0	0	0	0

write.table(tabla_P12,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P12.xlsx")

P12A_LLEGADA Año de llegada al país.

tabla_P12A_LLEGADA <- table(x$clave, x$P12A_LLEGADA, useNA = "no")

#write_xlsx(tabla_P12A_LLEGADA, "tabla_P12A_LLEGADA.xlsx")

a_12a <- head(tabla_P12A_LLEGADA,50)

kbl(a_12a) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	1950	1951	1952	1953	1954	1955	1956	1957	1959	1960	1961	1962	1963	1964	1965	1966	1967	1968	1969	1970	1971	1972	1973	1974	1975	1976	1977	1978	1979	1980	1981	1982	1983	1984	1985	1986	1987	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	9998	9999
10101011001	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	6	2	43	478	47
10101011002	2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	4	0	0	0	0	0	0	1	1	0	0	0	0	2	0	1	0	2	0	0	0	1	0	1	2	2	0	0	2	1	1	0	1	11	16	2831	57
10101021001	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	2	0	0	1	0	1	2	0	0	3	0	0	2	0	0	2	2	5	2	1	0	5	11	5	9	4	15	7	3814	56
10101021002	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	1	0	1	0	1	1	1	0	1	1	1	3	1	0	1	0	1	0	1	1	2	1	1	0	1	1	2	2	0	0	2	0	4	2	3	6	13	1012	36
10101021003	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	1	0	0	1	0	0	0	1	0	0	0	0	0	0	1	0	0	0	1	1	1	4	0	2	1	2	4	3	3	33	16	2152	63
10101021004	0	0	0	0	0	0	1	0	0	0	0	0	2	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	1	0	1	0	0	1	1	0	0	0	0	1	3	0	1	0	0	3	0	0	0	0	1	4	2	1	2	2	7	14	2	10	34	10	3191	93
10101021005	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	1	0	0	1	3	0	0	1	0	0	0	1	1	1	1	1	0	2	0	0	2	0	0	3	3	2	1	1	4	2	3	2	0	0	4	2	4	3	2	6	13	2460	32
10101031001	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	1	0	0	1	2	2	0	1	2	3	0	0	1	5	3	5	1	1	2	2	1	0	2	1	1	1	5	2	5	5	12	4328	133
10101031002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	1	1	0	2	0	0	1	0	1	1	1	1	1	1	1	2	1	1	0	3	1	0	0	3	2	1	1	0	0	0	6	2	1	0	2	0	8	2	0	4641	49
10101031003	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	0	0	0	1	0	1	3	1	0	0	0	0	0	0	0	1	0	1	0	2	0	0	0	1	0	0	1	1	2	0	0	4	6	1	4000	78
10101031004	1	0	0	0	0	1	0	0	0	0	1	0	1	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	2	1	1	0	0	4	2	1	0	0	0	0	0	0	0	1	0	3	5	3	1	4	0	2775	46
10101031005	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	1	1	1	0	1	0	0	2	2	1	1	3	2	2	2	0	1	3	1	0	1	1	3	1	0	4	1	2	0	1	2	0	2	3	1	6	5	5	4	5526	96
10101031006	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	1	0	2	0	0	0	0	0	1	0	0	0	1	0	1	0	0	0	2	1	0	0	0	0	2	1	1	1	1	2	0	0	1	0	4	0	0	1	0	2	0	2372	60
10101031007	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	1	0	1	1	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	2249	35
10101031008	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	2	0	2	0	0	0	1	0	0	0	1	0	0	3	0	0	0	0	1	0	0	1	1	1	1	0	0	0	0	0	0	1	0	2	6	1	1	3493	65
10101031009	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	1	0	2	0	0	0	0	0	1	0	2	1	2	2	1	0	0	0	0	0	1	1	3	3	0	1	0	0	0	1	1	1	1	1	2	0	0	1	1	4336	66
10101031010	0	0	0	0	0	0	1	0	0	0	0	2	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	0	0	3	0	0	0	0	2	2	0	0	0	0	2	0	1	1	0	4	0	0	2	1	0	0	0	0	0	0	0	0	3471	70
10101031011	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	2	1	0	1	0	2	0	3	0	0	1	0	1	1	0	0	0	2	0	0	0	0	1	0	0	1	0	2	2630	106
10101031012	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	1	2	1	2	1	0	0	0	1	0	0	1	1	0	1	0	0	0	0	0	0	1801	35
10101031013	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	3	0	0	1	0	1	1	0	1	0	0	0	0	0	3	1	1	1	0	0	1	2	2	4	0	0	3	3	3798	116
10101031014	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	2	1	0	1	0	2	0	0	1	0	0	0	0	0	0	4	2	1	0	1	0	2	6	2213	25
10101031015	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	1	0	0	0	0	1	0	0	1	1	0	0	0	1	2	2	2	0	1	1	2	1	1	2	1	0	0	4	3	4	1	8	2	1863	23
10101031016	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	1	1	0	0	0	0	1	0	1	0	0	3	1	0	0	0	2	1	2	1	7	1	4	0	0	3	0	1	0	0	1	1	0	3	5	10	2973	45
10101031017	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	1	1	0	0	1	0	1	1	1	0	2	2	1	0	0	0	0	1	2	0	1	3	2	1	0	1	1	0	0	0	2	1	2	2	2	0	4	4	3	3800	40
10101032002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	126	3
10101032011	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	4	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	411	7
10101032019	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	817	12
10101041001	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	1	0	0	1	1	0	1	0	0	0	1	2	0	3	2	2	0	0	2	2	3	2	0	6	6	3	4242	57
10101041002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	2	0	0	0	1	1	2	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	0	1	0	0	0	1	0	2104	52
10101041003	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	2	0	2	0	0	0	0	0	0	1	0	1	0	3	0	1	0	0	1	1	4	1	0	2	2	4	3	1	3	2	2	6	3	5	0	4	1	2	7	7	11	7	5021	89
10101042010	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	5	1
10101051001	1	1	1	0	1	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	2	0	0	0	1	0	0	0	0	0	1	2	1	0	1	0	0	0	0	0	1	0	2	1	2	0	0	0	1	0	1	0	0	1	1	2	2	2	2	3	2331	95
10101051002	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0	1	2	0	0	0	0	0	0	0	0	0	0	0	0	2	0	1875	29
10101051003	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	3	1	1	0	0	0	0	0	0	2	1	1	1	0	0	0	0	0	2	0	0	1	2	0	3	3	5	3149	93
10101051004	1	0	0	0	1	0	1	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	1	0	1	0	4	1	0	1	0	0	1	0	2	0	0	0	1	1	3	1	0	4	3	4	0	3	0	3	2	5	9	14	5	3455	102
10101061001	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	1	0	0	0	0	1	0	0	0	0	1	1	3	3	0	1	1	0	1	0	1	1	1	4	3	2	1	0	1	2	2	5	1	4	8	4	3	5	0	3	1	8	7	3	4	14	6	2	2	14	25	27	6522	86
10101061002	2	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	3	1	0	0	0	0	1	0	1	2	1	1	1	1	3	3	3	2	0	0	1	1	1	1	1	1	2	0	0	2	3	0	4	2	0	4	1	0	4	4	2	5	2632	30
10101061003	0	0	0	0	0	0	0	0	0	1	0	0	1	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	2	1	0	1	1	1	0	0	0	0	1	2	1	0	0	0	0	3	2	3	3	4	3569	66
10101061004	1	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	4	0	1	0	1	0	0	0	1	0	1	1	0	0	0	0	0	0	0	1	4	0	2909	65
10101061005	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	1	2	1	1	0	1	0	0	0	2	3	1	0	0	0	2	0	0	1	2	2	2	0	0	6	2	1	2489	48
10101061006	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	3	0	2	1	3	0	0	3	1	0	0	0	2	1	1	1	1	1	1	0	0	1	3	0	1	2	4	8	16	15	3977	80
10101061007	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	2	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	790	21
10101061008	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	2	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	1	0	0	5	0	0	0	0	3	0	0	1	1	0	1	1	0	0	0	2041	50
10101061009	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	2	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	166	0
10101061010	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1475	61
10101062003	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	154	3
10101062008	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	2	1	1	0	1	0	0	0	0	0	0	0	4	0	2	2	560	6
10101062013	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	3	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0	0	2	0	540	20
10101062029	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	46	1
10101062039	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	67	0

write.table(tabla_P12A_LLEGADA,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P12A_LLEGADA.xlsx")

P12A_TRAMO Período de llegada al País.

tabla_P12A_TRAMO <- table(x$clave, x$P12A_TRAMO, useNA = "no")

colnames(tabla_P12A_TRAMO) <- c("Entre 2010 y 2017","Entre 2000 y 2009","Entre 1990 y 1999","Antes de 1990","No aplica", "Missing")

#write_xlsx(tabla_P12A_TRAMO, "tabla_P12A_TRAMO.xlsx")

a_p12at <- head(tabla_P12A_TRAMO,50)

kbl(a_p12at) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Entre 2010 y 2017	Entre 2000 y 2009	Entre 1990 y 1999	Antes de 1990	No aplica	Missing
10101011001	58	1	1	5	478	41
10101011002	37	9	8	9	2831	47
10101021001	61	16	12	5	3814	45
10101021002	38	13	11	10	1012	23
10101021003	84	11	3	5	2152	39
10101021004	109	23	7	11	3191	50
10101021005	35	22	7	11	2460	29
10101031001	34	25	16	5	4328	122
10101031002	21	15	14	10	4641	39
10101031003	17	7	7	8	4000	68
10101031004	17	7	6	8	2775	43
10101031005	29	15	17	13	5526	90
10101031006	8	10	7	11	2372	52
10101031007	3	3	5	5	2249	27
10101031008	14	5	9	7	3493	57
10101031009	11	13	7	11	4336	58
10101031010	2	12	5	11	3471	65
10101031011	4	5	9	4	2630	105
10101031012	1	6	9	2	1801	30
10101031013	15	7	9	4	3798	112
10101031014	20	3	6	4	2213	19
10101031015	24	14	7	3	1863	19
10101031016	29	20	10	9	2973	30
10101031017	22	11	10	12	3800	30
10101032002	0	0	1	1	126	1
10101032011	1	6	2	0	411	6
10101032019	0	0	0	0	817	12
10101041001	24	11	8	8	4242	49
10101041002	4	4	4	5	2104	48
10101041003	42	32	14	14	5021	79
10101042010	0	0	0	0	5	1
10101051001	18	8	6	15	2331	85
10101051002	2	4	2	3	1875	27
10101051003	15	7	7	6	3149	88
10101051004	45	19	7	14	3455	93
10101061001	102	46	27	28	6522	62
10101061002	22	17	15	20	2632	23
10101061003	16	7	8	9	3569	59
10101061004	9	4	12	9	2909	52
10101061005	17	9	8	6	2489	42
10101061006	58	15	19	6	3977	55
10101061007	2	1	4	2	790	18
10101061008	4	13	7	3	2041	41
10101061009	0	2	0	0	166	0
10101061010	5	0	4	3	1475	56
10101062003	1	0	0	0	154	3
10101062008	8	5	3	1	560	4
10101062013	4	1	2	4	540	20
10101062029	0	0	0	0	46	1
10101062039	0	0	0	0	67	0

write.table(tabla_P12A_TRAMO,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P12A_TRAMO.xlsx")

Educacion

P13 ¿Asiste actualmente a la educación formal?

tabla_P13 <- table(x$clave, x$P13, useNA = "no")

colnames(tabla_P13) <- c("Sí","No asiste actualmente","Nunca asistió","Missing")

#write_xlsx(tabla_P10PAIS, "tabla_P10PAIS.xlsx")

a_013 <- head(tabla_P13,50)

kbl(a_013) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Sí	No asiste actualmente	Nunca asistió	Missing
10101011001	113	448	8	15
10101011002	923	1861	103	54
10101021001	1090	2670	119	74
10101021002	208	860	26	13
10101021003	577	1575	74	68
10101021004	936	2240	123	92
10101021005	823	1610	92	39
10101031001	1229	3042	125	134
10101031002	1522	2966	157	95
10101031003	1343	2454	222	88
10101031004	798	1879	128	51
10101031005	2105	3215	273	97
10101031006	726	1558	117	59
10101031007	874	1303	60	55
10101031008	1407	1988	104	86
10101031009	1580	2621	157	78
10101031010	1246	2109	145	66
10101031011	926	1650	113	68
10101031012	676	1066	48	59
10101031013	1226	2428	183	108
10101031014	699	1441	63	62
10101031015	737	1084	63	46
10101031016	1112	1731	136	92
10101031017	1447	2241	133	64
10101032002	38	80	7	4
10101032011	124	283	12	7
10101032019	249	526	46	8
10101041001	1237	2809	191	105
10101041002	661	1341	88	79
10101041003	1654	3225	212	111
10101042010	0	4	1	1
10101051001	592	1762	51	58
10101051002	565	1236	72	40
10101051003	946	2100	142	84
10101051004	1169	2281	80	103
10101061001	2520	3972	229	66
10101061002	1066	1549	86	28
10101061003	1132	2373	125	38
10101061004	1091	1745	80	79
10101061005	868	1566	68	69
10101061006	1481	2494	108	47
10101061007	246	507	41	23
10101061008	818	1153	83	55
10101061009	61	95	11	1
10101061010	535	896	69	43
10101062003	42	107	6	3
10101062008	175	376	19	11
10101062013	171	359	26	15
10101062029	7	36	3	1
10101062039	16	46	4	1

write.table(tabla_P13,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P13.xlsx")

P14 Curso o año más alto aprobado.

tabla_P14 <- table(x$clave, x$P14, useNA = "no")

colnames(tabla_P14) <- c( "0","1","2","3","4","5","6","7","8","No aplica","Missing")
#write_xlsx(tabla_P10PAIS, "tabla_P10PAIS.xlsx")

a_014 <- head(tabla_P14,50)

kbl(a_014) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	0	1	2	3	4	5	6	7	8	No aplica	Missing
10101011001	13	39	62	64	176	104	58	13	28	8	19
10101011002	143	265	357	317	921	270	195	62	246	103	62
10101021001	185	337	497	448	1246	334	255	130	325	119	77
10101021002	27	47	133	134	368	167	100	30	49	26	26
10101021003	72	172	296	271	765	237	161	48	143	74	55
10101021004	177	270	389	337	1008	274	260	101	323	123	129
10101021005	170	166	308	274	774	303	147	64	181	92	85
10101031001	211	319	508	472	1542	416	313	111	348	125	165
10101031002	292	349	622	553	1407	442	245	128	414	157	131
10101031003	292	359	506	367	1079	243	236	162	517	222	124
10101031004	170	222	352	332	847	214	171	80	278	128	62
10101031005	532	416	735	586	1883	487	184	112	334	273	148
10101031006	189	163	300	292	799	216	107	59	155	117	63
10101031007	172	168	299	251	784	201	98	60	146	60	53
10101031008	220	286	414	417	1252	301	140	89	216	104	146
10101031009	295	419	520	507	1412	369	186	108	374	157	89
10101031010	258	295	405	343	1029	195	180	127	479	145	110
10101031011	172	241	321	236	852	171	150	97	307	113	97
10101031012	105	114	212	212	625	210	88	61	100	48	74
10101031013	295	343	421	426	1092	257	196	187	410	183	135
10101031014	128	141	273	258	791	267	96	40	130	63	78
10101031015	153	143	234	242	547	291	98	47	74	63	38
10101031016	235	239	383	310	794	356	197	103	267	136	51
10101031017	351	282	502	381	1206	321	183	83	386	133	57
10101032002	3	12	16	12	36	16	11	4	9	7	3
10101032011	16	34	63	41	135	40	27	15	39	12	4
10101032019	49	68	101	80	232	59	59	33	98	46	4
10101041001	269	386	502	498	1203	348	239	141	451	191	114
10101041002	121	164	210	239	627	124	121	52	213	88	210
10101041003	415	272	563	544	1416	1054	275	133	169	212	149
10101042010	0	0	1	1	0	0	1	0	1	1	1
10101051001	98	149	334	275	690	357	182	80	143	51	104
10101051002	109	159	235	206	605	159	112	44	155	72	57
10101051003	185	270	362	354	894	240	229	117	356	142	123
10101051004	149	263	496	435	1045	527	227	99	187	80	125
10101061001	639	443	887	757	1425	1580	408	153	178	229	88
10101061002	158	196	401	293	641	462	163	86	159	86	84
10101061003	183	334	489	416	1044	446	244	84	238	125	65
10101061004	156	266	398	339	878	250	189	64	253	80	122
10101061005	167	190	310	262	709	365	148	72	198	68	82
10101061006	262	307	593	492	1036	772	221	108	161	108	70
10101061007	58	67	100	68	228	45	39	24	106	41	41
10101061008	231	129	243	259	588	293	72	36	91	83	84
10101061009	12	16	25	16	46	7	13	8	13	11	1
10101061010	125	132	171	145	359	104	91	71	213	69	63
10101062003	12	10	27	16	38	14	9	5	16	6	5
10101062008	44	37	89	58	125	102	49	18	25	19	15
10101062013	34	34	63	59	115	82	44	36	52	26	26
10101062029	1	3	0	2	14	6	2	5	10	3	1
10101062039	4	5	8	10	23	2	1	4	6	4	0

write.table(tabla_P14,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P14.xlsx")

P15 Nivel del curso más alto aprobado.

tabla_P15 <- table(x$clave, x$P15, useNA = "no")

colnames(tabla_P15) <- c( 

"Sala cuna o jardín infantil","Prekínder","Kínder","Especial o diferencial","Educación básica","Primaria o preparatorio (sistema antiguo)","Científico-humanista","Técnica profesional","Humanidades (sistema antiguo)","Técnica comercial, industrial/normalista (sistema
antiguo)","Técnico superior (1-3 años)","Profesional (4 o más años)","Magíster","Doctorado", "No aplica" , "Missing")


#write_xlsx(tabla_P15, "tabla_P15.xlsx")

a_015 <- head(tabla_P15,50)

kbl(a_015) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Sala cuna o jardín infantil	Prekínder	Kínder	Especial o diferencial	Educación básica	Primaria o preparatorio (sistema antiguo)	Científico-humanista	Técnica profesional	Humanidades (sistema antiguo)	Técnica comercial, industrial/normalista (sistema antiguo)	Técnico superior (1-3 años)	Profesional (4 o más años)	Magíster	Doctorado	No aplica	Missing
10101011001	9	4	0	0	39	7	105	66	26	4	61	221	21	4	8	9
10101011002	58	39	44	10	626	90	635	356	105	44	239	513	37	8	103	34
10101021001	80	46	58	12	1028	165	1054	516	89	21	249	454	16	0	119	46
10101021002	11	5	11	2	149	38	192	131	59	23	124	304	18	3	26	11
10101021003	34	16	22	8	376	103	541	298	101	43	220	409	13	3	74	33
10101021004	83	30	61	16	890	142	794	444	120	41	200	385	8	1	123	53
10101021005	71	41	58	5	526	53	543	265	57	21	204	535	42	8	92	43
10101031001	91	46	67	18	980	240	968	723	128	80	283	656	19	0	125	106
10101031002	145	53	92	17	1198	104	1149	610	60	23	381	666	18	1	157	66
10101031003	114	67	107	14	1646	106	901	524	16	7	149	161	2	0	222	71
10101031004	76	30	62	10	775	78	740	393	63	23	174	266	8	0	128	30
10101031005	242	126	161	13	1180	30	1331	859	30	13	541	763	25	2	273	101
10101031006	93	44	49	7	491	46	470	406	19	7	250	382	24	4	117	51
10101031007	64	43	62	6	518	20	627	360	20	7	213	248	8	0	60	36
10101031008	88	56	73	10	798	25	957	559	28	10	309	498	16	3	104	51
10101031009	142	57	91	14	1175	63	1162	586	42	26	374	485	8	0	157	54
10101031010	121	49	83	19	1291	66	838	456	28	16	180	203	1	0	145	70
10101031011	81	39	50	14	939	54	768	365	12	7	118	131	2	0	113	64
10101031012	41	23	40	3	395	23	445	214	17	17	189	325	11	2	48	56
10101031013	129	54	106	22	1380	77	931	485	37	18	178	260	6	0	183	79
10101031014	59	35	32	6	405	27	610	293	50	17	190	426	22	2	63	28
10101031015	57	43	51	4	391	10	388	219	12	4	232	409	24	1	63	22
10101031016	102	46	85	11	947	38	608	350	24	19	186	461	25	2	136	31
10101031017	141	86	119	10	1041	15	943	511	6	2	323	498	16	2	133	39
10101032002	0	2	1	0	42	4	26	19	0	0	7	20	0	0	7	1
10101032011	5	5	6	1	143	13	101	59	2	1	22	50	3	0	12	3
10101032019	15	19	15	0	318	37	163	141	0	0	36	33	2	0	46	4
10101041001	114	60	89	16	1444	181	1055	467	69	20	252	333	4	0	191	47
10101041002	51	19	50	12	655	97	527	282	19	17	132	144	3	2	88	71
10101041003	174	101	135	14	735	30	797	456	71	35	470	1721	145	17	212	89
10101042010	0	0	0	0	3	0	0	0	0	0	0	1	0	0	1	1
10101051001	49	18	28	4	376	66	438	227	112	50	264	641	71	10	51	58
10101051002	46	25	37	9	469	68	489	253	31	16	152	210	5	2	72	29
10101051003	84	33	66	15	1105	138	629	442	62	28	171	260	6	0	142	91
10101051004	68	34	45	10	561	72	686	387	95	36	345	1017	84	13	80	100
10101061001	311	146	178	9	948	24	781	395	57	28	633	2678	278	33	229	59
10101061002	82	36	39	5	575	36	427	215	38	13	156	851	121	14	86	35
10101061003	93	37	53	6	713	134	758	447	112	49	303	739	45	6	125	48
10101061004	73	38	42	10	670	123	606	372	64	29	201	602	11	1	80	73
10101061005	72	40	54	2	617	34	604	243	29	3	153	557	53	6	68	36
10101061006	110	59	90	9	631	22	675	341	58	27	455	1384	114	8	108	39
10101061007	21	15	20	3	269	21	196	105	9	3	44	40	0	0	41	30
10101061008	117	56	58	2	384	17	366	231	16	7	222	495	20	2	83	33
10101061009	6	2	4	1	61	2	44	19	2	0	9	7	0	0	11	0
10101061010	48	23	49	8	654	11	303	186	8	2	51	88	2	3	69	38
10101062003	8	3	1	0	50	3	33	18	3	0	7	19	3	0	6	4
10101062008	20	6	18	0	128	9	89	38	9	4	52	144	31	8	19	6
10101062013	10	9	14	1	154	13	86	53	3	3	21	135	19	6	26	18
10101062029	0	0	1	0	20	1	15	2	0	1	0	3	0	0	3	1
10101062039	2	0	2	0	21	0	10	15	1	0	8	4	0	0	4	0

write.table(tabla_P15,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P15.xlsx")

P15A Completó el nivel especificado.

tabla_P15A <- table(x$clave, x$P15A, useNA = "no")

colnames(tabla_P15A) <- c( 
"Sí","No","No aplica","Missing")
#write_xlsx(tabla_P15A, "tabla_P15A.xlsx")

a_015 <- head(tabla_P15A,50)

kbl(a_015) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Sí	No	No aplica	Missing
10101011001	424	133	8	19
10101011002	1642	1134	103	62
10101021001	1984	1790	119	60
10101021002	718	337	26	26
10101021003	1291	874	74	55
10101021004	1723	1434	123	111
10101021005	1463	934	92	75
10101031001	2505	1764	125	136
10101031002	2508	1968	157	107
10101031003	1746	2006	222	133
10101031004	1410	1244	128	74
10101031005	3157	2084	273	176
10101031006	1395	885	117	63
10101031007	1286	879	60	67
10101031008	1954	1424	104	103
10101031009	2303	1888	157	88
10101031010	1657	1671	145	93
10101031011	1301	1265	113	78
10101031012	1065	664	48	72
10101031013	1736	1912	183	114
10101031014	1337	806	63	59
10101031015	1124	702	63	41
10101031016	1505	1382	136	48
10101031017	2198	1502	133	52
10101032002	57	64	7	1
10101032011	198	208	12	8
10101032019	374	403	46	6
10101041001	1949	2125	191	77
10101041002	1015	923	88	143
10101041003	3349	1491	212	150
10101042010	1	3	1	1
10101051001	1513	816	51	83
10101051002	1026	770	72	45
10101051003	1505	1506	142	119
10101051004	2126	1298	80	129
10101061001	4268	2177	229	113
10101061002	1477	1104	86	62
10101061003	2002	1471	125	70
10101061004	1517	1295	80	103
10101061005	1431	996	68	76
10101061006	2459	1489	108	74
10101061007	393	351	41	32
10101061008	1190	760	83	76
10101061009	67	89	11	1
10101061010	663	757	69	54
10101062003	78	70	6	4
10101062008	334	215	19	13
10101062013	294	223	26	28
10101062029	31	12	3	1
10101062039	31	32	4	0

write.table(tabla_P15A,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P15A.xlsx")

Etnia

P16 Se considera perteneciente a un pueblo indígena u originario.

tabla_P16 <- table(x$clave, x$P16, useNA = "no")

colnames(tabla_P16) <- c( 
"Sí","No","Missing")


#write_xlsx(tabla_P16, "tabla_P16.xlsx")

a_P16 <- head(tabla_P16,50)

kbl(a_P16) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Sí	No	Missing
10101011001	68	507	9
10101011002	573	2286	82
10101021001	810	3098	45
10101021002	137	961	9
10101021003	413	1841	40
10101021004	713	2619	59
10101021005	441	2088	35
10101031001	797	3582	151
10101031002	948	3730	62
10101031003	1146	2882	79
10101031004	616	2180	60
10101031005	1120	4481	89
10101031006	539	1861	60
10101031007	496	1743	53
10101031008	723	2801	61
10101031009	1011	3376	49
10101031010	957	2538	71
10101031011	672	2016	69
10101031012	301	1509	39
10101031013	1011	2754	180
10101031014	324	1864	77
10101031015	246	1652	32
10101031016	692	2334	45
10101031017	742	3106	37
10101032002	6	110	13
10101032011	66	354	6
10101032019	81	727	21
10101041001	1024	3222	96
10101041002	489	1568	112
10101041003	454	4630	118
10101042010	0	4	2
10101051001	240	2114	109
10101051002	434	1393	86
10101051003	802	2351	119
10101051004	621	2900	112
10101061001	596	6123	68
10101061002	476	2223	30
10101061003	645	2981	42
10101061004	630	2300	65
10101061005	450	2090	31
10101061006	440	3598	92
10101061007	205	603	9
10101061008	345	1661	103
10101061009	63	105	0
10101061010	546	962	35
10101062003	20	133	5
10101062008	75	496	10
10101062013	130	399	42
10101062029	6	40	1
10101062039	21	46	0

write.table(tabla_P16,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P16.xlsx")

Pueblo indígena u originario listado.

tabla_P16A <- table(x$clave, x$P16A, useNA = "no")

colnames(tabla_P16A) <- c( 
"Mapuche","Aymara","Rapa Nui","Lican Antai","Quechua","Colla","Diaguita","Kawésqar","Yagán o Yamana","Otro","No aplica","Missing")

#write_xlsx(tabla_P16A, "tabla_P16A.xlsx")

a_P16A <- head(tabla_P16A,50)

kbl(a_P16A) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Mapuche	Aymara	Rapa Nui	Lican Antai	Quechua	Colla	Diaguita	Kawésqar	Yagán o Yamana	Otro	No aplica	Missing
10101011001	56	0	0	0	0	0	0	1	0	11	507	9
10101011002	508	1	5	0	0	1	2	3	1	52	2286	82
10101021001	745	7	0	0	1	0	2	0	0	55	3098	45
10101021002	124	3	0	0	1	0	2	0	0	7	961	9
10101021003	328	5	2	0	22	0	2	0	0	54	1841	40
10101021004	590	9	0	0	11	1	3	4	2	93	2619	59
10101021005	359	4	1	0	3	0	5	0	0	69	2088	35
10101031001	717	3	1	0	0	1	0	2	0	73	3582	151
10101031002	850	5	0	0	1	0	3	4	0	85	3730	62
10101031003	1061	3	0	0	2	0	0	5	1	74	2882	79
10101031004	536	0	0	0	0	0	3	0	0	77	2180	60
10101031005	1000	9	2	3	3	0	7	1	2	93	4481	89
10101031006	494	1	0	0	0	1	0	0	0	43	1861	60
10101031007	444	4	0	0	2	0	1	1	1	43	1743	53
10101031008	648	1	0	0	1	2	7	0	0	64	2801	61
10101031009	914	3	1	0	0	2	1	3	4	83	3376	49
10101031010	901	6	1	0	0	0	3	1	0	45	2538	71
10101031011	624	4	0	0	0	0	3	6	2	33	2016	69
10101031012	268	3	1	0	0	0	2	0	2	25	1509	39
10101031013	941	2	2	0	1	0	2	1	0	62	2754	180
10101031014	285	0	1	0	0	0	4	1	0	33	1864	77
10101031015	206	10	0	0	0	0	1	0	1	28	1652	32
10101031016	636	0	1	0	4	0	1	2	0	48	2334	45
10101031017	671	5	2	1	1	1	2	5	0	54	3106	37
10101032002	6	0	0	0	0	0	0	0	0	0	110	13
10101032011	56	0	0	0	0	0	0	0	0	10	354	6
10101032019	73	0	1	0	0	0	0	0	0	7	727	21
10101041001	912	1	1	0	1	0	5	1	5	98	3222	96
10101041002	447	2	0	0	1	0	0	1	0	38	1568	112
10101041003	382	1	2	2	4	0	2	2	1	58	4630	118
10101042010	0	0	0	0	0	0	0	0	0	0	4	2
10101051001	212	2	3	0	0	2	6	0	0	15	2114	109
10101051002	387	1	0	0	0	0	1	0	0	45	1393	86
10101051003	729	0	1	0	0	0	0	6	0	66	2351	119
10101051004	545	8	1	0	0	2	0	0	0	65	2900	112
10101061001	498	7	1	0	0	0	0	1	0	89	6123	68
10101061002	425	1	1	0	0	0	3	2	0	44	2223	30
10101061003	582	5	0	0	2	0	3	9	0	44	2981	42
10101061004	553	8	0	1	1	0	0	2	1	64	2300	65
10101061005	396	2	0	0	0	2	4	1	0	45	2090	31
10101061006	382	0	0	0	0	0	2	0	0	56	3598	92
10101061007	183	5	0	0	0	0	1	0	0	16	603	9
10101061008	305	4	2	0	0	0	2	0	0	32	1661	103
10101061009	57	0	0	0	0	0	0	0	0	6	105	0
10101061010	517	7	0	0	0	0	0	0	0	22	962	35
10101062003	14	0	0	0	0	0	0	0	0	6	133	5
10101062008	59	2	0	0	0	0	1	2	0	11	496	10
10101062013	128	0	0	0	0	0	0	0	0	2	399	42
10101062029	6	0	0	0	0	0	0	0	0	0	40	1
10101062039	21	0	0	0	0	0	0	0	0	0	46	0

write.table(tabla_P16A,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P16A.xlsx")

P16A_OTRO Pueblo indígena u originario (Otro).

Atencion: hay que correr este pedazo de codigo una vez se cargue la tabla original.

tabla_P16A_OTRO <- table(x$clave, x$P16A_OTRO, useNA = "no")

colnames(tabla_P16A_OTRO) <- c(
"Lafquenche","Pehuenche","Huilliche","Picunche","Changos","Chonos","Ona","Tehuelches","Pueblos de América Latina","Pueblos del resto del mundo","Afrodescendiente","Otros pueblos presentes en el territorio nacional","Pueblo no declarado","No aplica","Missing")


#write_xlsx(tabla_P16A_OTRO, "tabla_P16A_OTRO.xlsx")

a_P16A_OTRO <- head(tabla_P16A_OTRO,50)

kbl(a_P16A_OTRO) %>%
  kable_styling(bootstrap_options = c("striped", "hover")) %>%
  kable_paper() %>%
  scroll_box(width = "100%", height = "300px")

	Lafquenche	Pehuenche	Huilliche	Picunche	Changos	Chonos	Ona	Tehuelches	Pueblos de América Latina	Pueblos del resto del mundo	Afrodescendiente	Pueblo no declarado	No aplica	Missing
10101011001	0	0	10	0	0	0	0	0	0	0	0	1	564	9
10101011002	0	1	41	0	0	4	1	0	1	1	0	3	2807	82
10101021001	0	0	37	0	0	0	1	0	0	0	2	15	3853	45
10101021002	0	0	6	0	0	0	0	0	0	0	0	1	1091	9
10101021003	0	0	42	0	0	0	0	2	1	0	0	9	2200	40
10101021004	0	0	59	0	0	0	0	0	8	0	0	26	3239	59
10101021005	0	1	38	0	0	0	0	0	4	4	0	22	2460	35
10101031001	0	0	43	0	0	0	0	0	2	1	0	27	4306	151
10101031002	0	0	47	2	0	0	0	0	0	6	0	30	4593	62
10101031003	0	0	45	0	0	0	0	0	1	1	0	27	3954	79
10101031004	0	0	59	0	0	1	0	0	0	0	0	17	2719	60
10101031005	0	1	58	0	0	2	1	0	0	0	0	31	5508	89
10101031006	0	1	31	0	1	0	1	0	0	2	0	7	2357	60
10101031007	0	0	29	1	0	2	0	0	0	0	0	11	2196	53
10101031008	0	0	38	0	0	0	0	0	0	0	0	26	3460	61
10101031009	0	1	41	0	0	2	2	1	1	0	0	35	4304	49
10101031010	1	0	23	0	0	0	0	0	0	0	0	21	3450	71
10101031011	0	0	18	0	0	0	0	0	0	0	1	14	2655	69
10101031012	0	0	19	0	0	0	0	0	0	0	0	6	1785	39
10101031013	0	0	23	0	0	0	1	0	0	0	2	36	3703	180
10101031014	0	0	20	0	0	0	0	0	1	1	0	11	2155	77
10101031015	0	0	25	0	0	0	0	0	0	0	0	3	1870	32
10101031016	0	0	22	0	0	1	0	0	0	0	0	25	2978	45
10101031017	0	0	40	0	0	1	0	1	0	0	0	12	3794	37
10101032002	0	0	0	0	0	0	0	0	0	0	0	0	116	13
10101032011	0	0	3	0	0	0	1	0	0	0	0	6	410	6
10101032019	0	0	1	0	0	0	0	0	0	0	0	6	801	21
10101041001	0	4	67	0	1	0	0	0	0	0	0	26	4148	96
10101041002	0	0	23	0	0	0	0	0	0	0	0	15	2019	112
10101041003	0	0	37	0	0	1	0	0	0	1	1	18	5026	118
10101042010	0	0	0	0	0	0	0	0	0	0	0	0	4	2
10101051001	0	0	7	0	1	0	1	0	0	0	0	6	2339	109
10101051002	0	0	32	0	0	0	0	0	0	0	0	13	1782	86
10101051003	0	0	41	0	0	0	0	0	0	0	2	23	3087	119
10101051004	0	0	46	0	0	0	1	1	0	0	0	17	3456	112
10101061001	1	3	66	0	0	1	0	1	0	0	0	17	6630	68
10101061002	0	0	29	0	0	0	1	0	1	2	2	9	2655	30
10101061003	0	0	35	0	0	0	0	0	0	1	1	7	3582	42
10101061004	0	0	46	0	0	1	1	0	0	1	0	15	2866	65
10101061005	0	0	8	0	0	0	0	0	0	14	0	23	2495	31
10101061006	0	0	44	0	0	0	1	0	0	0	1	10	3982	92
10101061007	0	0	11	0	0	0	0	0	0	0	0	5	792	9
10101061008	0	0	22	0	0	0	0	0	0	0	1	9	1974	103
10101061009	0	0	6	0	0	0	0	0	0	0	0	0	162	0
10101061010	0	0	14	0	0	0	0	1	0	0	0	7	1486	35
10101062003	0	0	6	0	0	0	0	0	0	0	0	0	147	5
10101062008	0	0	7	0	0	0	0	0	0	0	3	1	560	10
10101062013	0	0	1	0	0	0	0	0	0	0	0	1	527	42
10101062029	0	0	0	0	0	0	0	0	0	0	0	0	46	1
10101062039	0	0	0	0	0	0	0	0	0	0	0	0	67	0

write.table(tabla_P16A_OTRO,"tabla_TIPO_OPERATIVO_df.txt", col.name = NA)
tabla <- read.table("tabla_TIPO_OPERATIVO_df.txt")
tabla_names <- tabla[1,]
colnames(tabla) <- tabla_names
tabla <- tabla[-1,]
names(tabla)[1] <- "Clave"
write_xlsx(tabla,"tablas_2017_personas/tabla_P16A_OTRO.xlsx")

Análisis de frecuencias en el Censo de Personas 2017 de Chile

VE-CC-CF

Miércoles 1-06-2021